Stat CH 1 Homework 1.1a Sampling and Parameters Study

Which of the following scenarios contains a sampling error? A study is conducted to determine the favorite subject of all the students in your high school. Students in your homeroom class were used as the sample. A study is conducted about where the best travel destinations are - Europe or Asia. People who live in big cities throughout Europe were used as the sample. A hospital conducts a study about a new heart monitoring software. All patients who use the software were used as the sample. A study is conducted by a cereal manufacturer about two brands of cereal, and a question on a survey read, "Do you prefer the delicious taste of Brand X or the taste of Brand Y?"

A study is conducted to determine the favorite subject of all the students in your high school. Students in your homeroom class were used as the sample.

Sharon wants to estimate the percentage of parents that use cloth diapers. She asks a randomly selected group of 75 parents whether or not they use cloth diapers. What is the population? the 75 people surveyed specific "yes" or "no" responses to the survey the percentage of surveyed parents that use cloth diapers the percentage of all parents that use cloth diapers all parents

All parents

Which of the following sampling scenarios describe convenience sampling? The freshman, sophomore, junior, and senior years were numbered one, two, three, and four respectively. A random number generator was used to pick two of those years. All students belonging to those two years were in the sample. An administrative assistant was asked to stand in front of the library one Wednesday and ask the first 100 undergraduate students he encountered what they paid for tuition for the Fall semester. Those 100 students were the sample.

An administrative assistant was asked to stand in front of the library one Wednesday and ask the first 100 undergraduate students he encountered what they paid for tuition for the Fall semester. Those 100 students were the sample.

A scientist is interested in finding out the effect of soil quality on crop quality. Would an experimental or observational study design be more appropriate? An experimental study should be used with the crop quality as the controlled factor. An observational study should be used because the soil quality cannot be controlled. An experimental study should be used with the soil quality as the controlled factor. An observational study should be used because the crop quality cannot be directly controlled.

An experimental study should be used with the soil quality as the controlled factor. An experimental study should be used because the goal involves a cause and effect relationship.

A researcher wants to evaluate the effect of using Facebook on happiness. Would an experimental or observational study design be more appropriate? An experimental study should be used with the use of Facebook as the controlled factor. An experimental study should be used with happiness as the controlled factor. An observational study should be used because it is not possible to control the use of Facebook. An observational study should be used because it is not possible to control happiness.

An experimental study should be used with the use of Facebook as the controlled factor. An experimental study should be used because the researcher is attempting to control one or more aspects of the individuals in the sample.

A researcher is interested in the effects of watching videos just before bed on the quality of sleep. He has decided to test the claim "Watching 1 hour of video just before going to bed reduces the number of minutes of REM sleep by more than 10%. " Which of the following data collection processes would be appropriate? Select only one answer choice. Choose a random sample of people and ask them how many hours of video they watched last night and how much REM sleep they had. Choose a random sample of people. Randomly select half of them and have them watch one hour of video just before going to bed, and then monitor their sleep. Have the other half not watch any video and monitor their sleep. Choose a random sample of people. On multiple randomly selected nights, randomly assign each person to either watch one hour of video or not watch video and monitor their sleep. Choose a random sample of people. On multiple randomly selected nights, measure the amount of video they watch and monitor their sleep.

Choose a random sample of people. On multiple randomly selected nights, randomly assign each person to either watch one hour of video or not watch video and monitor their sleep. To perform an experiment, a control group that does not watch video and a test group that does should be used. It is also important for the process to account for possible confounding variables. In this case both the person and the night of the week could be confounding variables. By choosing random nights and having the same people either watch 1 hour of videos or not, variations due to the person and the night of the week should not interfere with the analysis.

Which of the following scenarios contain nonbiased samples? Select all that apply. Christine wants to estimate the mean grade point average of students at her school. She collects data by recording the grade point average of every 25th student on the list of students after a randomly selected first student. Homer wants to estimate the ethnic background distribution of residents of his town. He collects data from 1000 randomly selected town residents by using a random number generator. To estimate the mean height of students at her grade school, Tammy collects data by selecting a random group of students within her classroom. To estimate the mean salary of professors at his university, Peter collects data by recording the salaries of all professors included in 12 randomly selected departments.

Christine wants to estimate the mean grade point average of students at her school. She collects data by recording the grade point average of every 25th student on the list of students after a randomly selected first student. Homer wants to estimate the ethnic background distribution of residents of his town. He collects data from 1000 randomly selected town residents by using a random number generator. To estimate the mean salary of professors at his university, Peter collects data by recording the salaries of all professors included in 12 randomly selected departments. A sample is biased if some individuals of the population are more or less likely to be selected than others. The sample from choice A is nonbiased because every student has an equal chance of being selected. The sample from choice B is nonbiased because every resident has an equal chance of being selected. The sample from choice D is nonbiased because every professor has an equal chance of being selected.

Which of the following scenarios contain nonbiased samples? Select all that apply. Christopher wants to estimate the male to female ratio of the residents of his city. He collects data by recording the sex of every 50th resident after selecting a random starting point on a list of residents. Ruby wants to estimate the mean grade point average of students at her school. She collects data by recording the grade point average of every 25th student on the list of students after a randomly selected first student. To estimate the mean salary of professors at his university, Benjamin collects data by recording the salaries of all professors included in 12 randomly selected departments. To estimate the mean number of calories consumed by students at her school, Mary collects data from randomly selected individuals in the cafeteria for breakfast.

Christopher wants to estimate the male to female ratio of the residents of his city. He collects data by recording the sex of every 50th resident after selecting a random starting point on a list of residents. Ruby wants to estimate the mean grade point average of students at her school. She collects data by recording the grade point average of every 25th student on the list of students after a randomly selected first student. To estimate the mean salary of professors at his university, Benjamin collects data by recording the salaries of all professors included in 12 randomly selected departments. A sample is biased if some individuals of the population are more or less likely to be selected than others. The sample from choice A is nonbiased because every resident has an equal chance of being selected. The sample from choice B is nonbiased because every student has an equal chance of being selected. The sample from choice C is nonbiased because every professor has an equal chance of being selected.

To study the mean blood pressure of all people in her state, Christine samples the population by dividing the residents by towns and randomly selecting 9 of the towns. She then collects data from all the residents in the selected towns. Which type of sampling is used? Convenience sampling Systematic sampling (involves selecting every nth individual from the list of individuals in the population based on a randomly selected starting position.) Cluster sampling Stratified sampling

Cluster sampling This scenario demonstrates cluster sampling. Cluster sampling involves dividing the population into groups and randomly selecting several of these groups.

To study the mean respiratory rate of all people in his state, Frank samples the population by dividing the residents by towns and randomly selecting 12 of the towns. He then collects data from all the residents in the selected towns. Which type of sampling is used? Convenience sampling Systematic sampling Stratified sampling Cluster sampling

Cluster sampling This scenario demonstrates cluster sampling. Cluster sampling involves dividing the population into groups and randomly selecting several of these groups.

To study the mean head size of all people in her state, Jacqueline collects data from 20 people in her town. Which type of sampling is used? Cluster sampling Stratified sampling Systematic sampling Convenience sampling

Convenience sampling This scenario demonstrates convenience sampling. Convenience sampling involves selecting individuals from the population that are easily accessible, or from which data is easily obtained.

Angela is studying the mean blood pressure of all students attending her college. She collects data from the 38 students in her statistics class. Which type of sampling is used? Cluster sampling Stratified sampling Systematic sampling Convenience sampling

Convenience sampling This scenario demonstrates convenience sampling. Convenience sampling involves selecting individuals from the population that are easily accessible, or from which data is easily obtained.

Samplings

Convenience sampling: a type of sampling that is not random and involves using a population that is readily available.A related term is Quota sampling: using a sample that is selected to match the population with respect to some specific characteristic(s). Cluster sampling: dividing the population into groups, and then randomly selecting some of the groups. All the members from these chosen groups are in the cluster sample. Systematic sampling: randomly selecting a starting point in a list of names and take every nth piece of data from a listing of the population. Systematic samples are a special subset of cluster samples. Stratified sampling: dividing the population into groups, and then taking your sample from a proportionate number from each group

Jason is collecting data on the number of books students read each year. What type of data is this? Angela is collecting data on the number of classes that students take. What type of data is this? Timothy is collecting data on the number of dental cavities. What type of data is this? Patrick is collecting data on shoe sizes available at a shoe store. What type of data is this? qualitative discrete quantitative continuous quantitative none of the above

Discrete is defined as the type of quantitative data that is the result of counting.

Is the statement below true or false?A sample is all individuals, objects, or measurements whose properties are being studied. True False

False A population is defined as all individuals, objects, or measurements whose properties are being studied. A sample is defined as a subset of the population studied.

Is the statement below true or false? A sampling error is the situation in which not all members of the population are equally likely to be selected.

False A sampling error is defined as the natural variation that results from selecting a sample to represent a larger population.

True or False? An explanatory variable is a value or component of the independent variable applied in an experiment.

False An explanatory variable is defined as the independent variable in an experiment. The value or component of the independent variable applied in an experiment is called the treatment.

In reference to different sampling methods, is the following statement true or false? Cluster sampling includes the steps: divide the population into groups; use simple random sampling to identify a proportionate number of individuals from each group. True or False?

False Cluster sampling includes the steps: use simple random sampling to select a set of groups; every individual in the chosen groups is included in the sample. Stratified sampling includes the steps: divide the population into groups; use simple random sampling to identify a proportionate number of individuals from each group.

True or False? A sampling bias is the natural variation that results from selecting a sample to represent a larger population.

False A sampling bias is defined as the situation in which not all members of the population are equally likely to be selected.

True or False? Stratified sampling was used in the scenario below. A random number generator is used to select a student from the alphabetical listing of all undergraduate students in the Fall semester. Starting with that student, every 50th student is chosen until 75 students are included in the sample.

False, this is an example of systematic sampling

A chef keeps track of the temperature of his refrigerator in degrees Celsius. What is the level of measurement of the data? Nominal Ordinal Interval Ratio

Interval This is interval data because degrees Celsius is a numerical scale where differences are meaningful. However, because Celsius does not have a true zero value, it is not ratio data.

A new mother keeps track of the time when her baby wakes up each morning. What is the level of measurement of the data? Nominal Ordinal Interval Ratio

Interval This is interval data because time of day is a numerical scale where differences are meaningful. However, because the time of day does not have a true zero value, it is not ratio data.

Which of the following scenarios demonstrates sampling bias? To estimate the ethnic background distribution of residents of her town, Susan collects data from 1000 randomly selected town residents by using a random number generator. Kathryn wants to estimate the mean amount of money spent on clothes per week by mall shoppers. She collects data from every 10th person entering a clothing store at the mall. Brenda wants to estimate the mean grade point average of students at her school. She collects data by recording the grade point average of every 25th student on the list of students after a randomly selected first student. To estimate the mean salary of professors at his university, Ryan collects data by recording the salaries of all professors included in 12 randomly selected departments.

Kathryn wants to estimate the mean amount of money spent on clothes per week by mall shoppers. She collects data from every 10th person entering a clothing store at the mall. A sample is biased if some individuals of the population are more or less likely to be selected than others. The sample from choice B is biased because mall shoppers that do not visit this particular store are not represented.

Select all of the following scenarios below that contain biased samples. Kelly wants to estimate the mean number of calories consumed by students at her school. She collects data from randomly selected individuals in the cafeteria for breakfast. To estimate the ethnic background distribution of residents of her town, Deborah collects data from 1000 randomly selected town residents by using a random number generator. To estimate the mean amount of money spent on clothes per week by mall shoppers, Paul collects data from every 10th person entering a clothing store at the mall. Homer wants to estimate the mean grade point average of students at his school. He collects data by recording the grade point average of every 25th student on the list of students after a randomly selected first student.

Kelly wants to estimate the mean number of calories consumed by students at her school. She collects data from randomly selected individuals in the cafeteria for breakfast. To estimate the mean amount of money spent on clothes per week by mall shoppers, Paul collects data from every 10th person entering a clothing store at the mall. A sample is biased if some individuals of the population are more or less likely to be selected than others. The sample from choice A is biased because students that do not eat breakfast are not included in the sample. The sample from choice C is biased because mall shoppers that do not visit this particular store are not represented.

A statistics student is doing a project for her class. She wants to make a prediction for the outcome of an upcoming national election. Since there are only two candidates, she decides that her question is "Which candidate do more people favor in the upcoming election?" She decides to randomly interview 100 students crossing the courtyard on campus about their preference. Is this sample good for drawing general conclusions about the results of the election?

No. The results are not generalizable because the students at her school are not representative of the population of all voters. Since the students at a college are not representative of the population of a country as a whole, even a well-chosen random sample of the students is not generalizable to the whole population. The results should not be considered useful for predicting the outcome of the election.

A statistics student is doing a project for her class. She wants to make a prediction for the outcome of an upcoming national election. Since there are only two candidates, she decides that her question is "Which candidate do more people favor in the upcoming election?" She decides to randomly interview 100 students crossing the courtyard on campus about their preference. Is this sample good for drawing general conclusions about the results of the election? Yes. Since the people in the sample are chosen randomly, the sample should represent the population. No. The results are not generalizable because the students at her school are not representative of the population of all voters. No. The results are not generalizable because too few people are interviewed. No. The results are not generalizable because too many people are interviewed.

No. The results are not generalizable because the students at her school are not representative of the population of all voters. Since the students at a college are not representative of the population of a country as a whole, even a well-chosen random sample of the students is not generalizable to the whole population. The results should not be considered useful for predicting the outcome of the election.

A restaurant surveys its patrons to pick their favorite item on the menu. What is the level of measurement of the data? Nominal Ordinal Interval Ratio

Nominal This is nominal data because the menu items do not have an order to them. Even though a person may have a personal preference, there is no ranking that is universal.

A hotel asks its patrons to fill out a customer satisfaction survey to rate the service. The options are Very Dissatisfied, Somewhat Dissatisfied, Somewhat Satisfied, Very Satisfied. What is the level of measurement of the data? Nominal Ordinal Interval Ratio

Ordinal This is ordinal data because the values are ordered, but do not have a meaningful numerical value.

A biologist samples and measures the length of the fish in a lake. What is the level of measurement of the data? Nominal Ordinal Interval Ratio

Ratio This is ratio data because length has a true zero, and ratios of lengths are meaningful.

A track runner keeps track of how long it takes her to run the 200 meter dash. What is the level of measurement of the data? A biologist samples and measures the length of the fish in a lake. What is the level of measurement of the data? Nominal Ordinal Interval Ratio

Ratio This is ratio data because length of time has a true zero, and ratios are meaningful. If someone took twice as long to run the 200 meters, then that person ran half as fast.

A track runner keeps track of how long it takes her to run the 200 meter dash. What is the level of measurement of the data? Nominal Ordinal Interval Ratio

Ratio This is ratio data because length of time has a true zero, and ratios are meaningful. If someone took twice as long to run the 200 meters, then that person ran half as fast.

A market researcher finds the price of several brands of fabric softener. What is the level of measurement of the data? Nominal Ordinal Interval Ratio

Ratio This is ratio data because price has a true zero, and ratios of prices are meaningful.

A zoologist measures the birthweight of each cub in a litter of lions. What is the level of measurement of the data? Nominal Ordinal Interval Ratio

Ratio This is ratio data because weight has a true zero, and ratios of weights are meaningful.

Sample errors and bias

Sampling error: the error caused by the actual process of sampling that varies from sample to sample because the sample is not the whole population Non-sampling error: the error caused by factors not related to the sampling process Bias: when an individual's opinion or preference influences the results of a sample Sampling bias: errors that can occur in research studies by not properly selecting participants for the study and created when a sample is collected from a population, where some members of the population are not as likely to be chosen as othersSampling bias is also commonly referred to as selection bias

In order to study the wrist sizes of people in her town, Kathryn samples the population by dividing the residents by age and randomly selecting a proportionate number of residents from each age group. Which type of sampling is used? Cluster sampling Convenience sampling Stratified sampling Systematic sampling

Stratified sampling This scenario demonstrates stratified sampling. Stratified sampling involves dividing the population into groups and randomly selecting a proportionate number of individuals from each group

Donald is studying the eating habits of all students attending his school. He samples the population by dividing the students into groups by grade level and randomly selecting a proportionate number of students from each group. He then collects data from the sample. Which type of sampling is used? Systematic sampling Convenience sampling Stratified sampling Cluster sampling

Stratified sampling This scenario demonstrates stratified sampling. Stratified sampling involves dividing the population into groups and randomly selecting a proportionate number of individuals from each group.

In order to study the shoe sizes of people in his town, Billy samples the population by dividing the residents by age and randomly selecting a proportionate number of residents from each age group. Which type of sampling is used? Systematic sampling Stratified sampling Convenience sampling Cluster sampling

Stratified sampling This scenario demonstrates stratified sampling. Stratified sampling involves dividing the population into groups and randomly selecting a proportionate number of individuals from each group.

A consumer research company is interested in determining if a certain company's new refrigerator model is more efficient than the older model. Researchers decide to investigate the claim that the new model uses 10% less electricity than the older model for the same cooling load. Which data collection method is appropriate? Select only one answer choice. The company should obtain random samples of people who own each model and measure the electricity used over one month for each refrigerator. The company should obtain random samples of each model, place them in similar conditions, fill them with the same amount of water bottles, and monitor their electrical usage over one month. The company should get a random sample of the new model, place them all in similar conditions, fill them with the same number of water bottles, and monitor their electrical usage over one month. The company should obtain one new model and one old model, place them both in the same room, fill them with the same number of water bottles, and monitor their electrical usage over one month.

The company should obtain random samples of each model, place them in similar conditions, fill them with the same amount of water bottles, and monitor their electrical usage over one month. A random sample of both models needs to be used to account for variation in the individual units. The cooling loads should also be equivalent, so they should be in similar conditions with similar contents.

A study was performed with a random sample of 5 people from a certain city. What population would be appropriate for generalizing conclusions from the study, assuming the data collection methods used did not introduce biases? The conclusions should be restricted to only the city that was sampled. The conclusions are generalizable to all people on Earth. The conclusions are generalizable to all people in the country. The conclusions apply only to the sample. The conclusions apply to people in any city.

The conclusions apply only to the sample. The sample size is very small, so it is not likely to be representative of the city or any larger population.

A study was performed with a random sample of 200 people from one college. What population would be appropriate for generalizing conclusions from the study, assuming the data collection methods used did not introduce biases? The conclusions should apply to all people in the same country. The conclusions should apply to all people within the same city as the college. The conclusions should apply to people at that particular college. The conclusions should apply to people at any college. The conclusions apply only to the sample.

The conclusions should apply to people at that particular college. The sample should represent people at that college reasonably well because it is not very small and was randomly chosen from all the people there. However, the population of that college is probably not representative of the population in any larger context, so further generalization should not be used.

A cell phone company advertises that their average plan rate is $73. Given that their plan rates are $9, $82, $95, and $106, why is this statistic misleading? The statistic contains a calculation error. The sample is biased. The data contains an outlier. The sample size is insufficient

The data contains an outlier. The average of these plan rates is accurate, but the advertised average is misleading because so many of the plan rates are well above this level. The very low plan rate is an outlier and brings the average down to a misleading value.

A candy manufacturer is interested in the distribution of colors in each of its packages of candy sold. The manufacturer wants to answer the question "What is the typical distribution of colors in a package of candy?" Which data collection method should be used?

The manufacturer should randomly sample packages at the factory over multiple batches and determine the distribution in each package. To determine a typical distribution, multiple packages are needed. The packages should be representative of all packages produced at the factory, so randomly chosen packages from multiple batches would be best.

Thomas wants to estimate the mean height of students attending his college. He records the heights of 25 randomly selected students attending the college. What is the parameter? the heights of the randomly selected students the mean height of all students attending the college the mean height of the randomly selected students the 25 randomly selected students all the students attending the college

The mean height of all students attending the college A parameter is a number that is used to represent a population characteristic. In this case, the parameter is the mean height of all students attending the college.

A consumer research company is interested in determining if a certain company's new refrigerator model is more efficient than the older model. Which might be an appropriate claim to result from this research? The new refrigerator model is more efficient than the old model. The new refrigerator model uses 10% less electricity for the same cooling load. The new refrigerator model uses about 0.5 kW/hr per day. The new refrigerator model costs less to operate than the old model.

The new refrigerator model uses 10% less electricity for the same cooling load. The claim should be testable and relevant to the goal of the research. Since the goal is to investigate the relative efficiency, the claim should make a quantitative statement about the efficiency. It is important to also specify that the cooling to be done should be the same. FEEDBACK

A researcher is interested in the effects of watching videos just before bed on the quality of sleep. He has decided to test the claim "Watching 1 hour of video just before going to bed reduces the number of minutes of REM sleep by more than 10%." How should the number of hours of video be treated? The number of hours of video should be measured for each person in the sample because variation in the amount could affect REM sleep differently. The number of hours of video should be controlled. Some measurements should be done for 1 hour of video and some should be done with no video. The number of hours of video should be controlled. All people in the sample should be asked to watch 1 hour of video. The number of hours of video should be controlled. All people in the sample should be asked to watch no video before bed.

The number of hours of video should be controlled. Some measurements should be done for 1 hour of video and some should be done with no video. The number of hours of video is an experimental factor that needs to be controlled. The claim specifies 1 hour. So there should be a test set for people who watched 1 hour of video and a control set for people who watched no video.

Rebecca collected data from a random sample of 500 homeowners in her state asking whether or not they use electric heat. Based on the results, she reports that 51% of the homeowners in the nation use electric heat. Why is this statistic misleading? The sample size is insufficient. The statistic contains a calculation error. The sample is biased. The data contains an outlier.

The sample is biased. The sample in this case is biased. The individuals included in the sample are not representative of the entire population because heating methods may be different based on different regions of the country.

Tina collected data from a random sample of 600 students in her university asking whether or not they exercise more than 30 minutes per day. Based on the results, she reports that 53% of the students in the nation exercise more than 30 minutes per day. Why is this statistic misleading?

The sample is biased. The sample in this case is biased. The individuals included in the sample are not representative of the entire population because the students at her school do not necessarily have the same exercise habits as the entire national student population.

Kenneth collected data from a random sample of 800 voters in his city asking whether or not they would vote to reelect the current governor. Based on the results, he reports that 64% of the voters in his state would vote to reelect the current governor. Why is this statistic misleading? The sample size is insufficient. The sample is biased. The statistic contains a calculation error. The data contains an outlier.

The sample is biased. The sample in this case is biased. The individuals included in the sample are not representative of the entire population because the voters in his city do not necessarily have the same opinion as the rest of the state.

After asking 11 randomly selected athletes from his school whether or not they eat raw eggs , Andrew reports that 36% of the athletes from his school eat raw eggs based on his survey. Why is this statistic misleading? The sample size is insufficient. The sample is biased. The statistic contains a calculation error. The data contains an outlier.

The sample size is insufficient. Although the sampling was random, using such a small sample size to draw conclusions about a much larger number of individuals is bound to be unreliable. This sample size is too small.

After asking 11 randomly selected students from her school whether or not they read the newspaper , Gloria reports that 55% of the students from her school read the newspaper based on her survey. Why is this statistic misleading?

The sample size is insufficient. Although the sampling was random, using such a small sample size to draw conclusions about a much larger number of individuals is bound to be unreliable. This sample size is too small.

A farmer divided his land into 2 groups of sections randomly. There is no difference in the quality of the soil between the 2 groups of land. He used Type A seeds in the first group and Type B seeds in the second group. After 3 months, the heights of the crops are measured across the two groups of land sections. Is the study observational or experimental? If it is an experiment, what is the controlled factor? The study is an observational study. The study is an experiment. The controlled factor is the seed type. The study is an experiment. The controlled factor is the land. The study is an experiment. The controlled factor is the growth of the crops.

The study is an experiment. The controlled factor is the seed type. Since the land is divided into two groups and each group is treated with a different type of seed, the study is an experiment. The type of seed is the controlled factor.

In a study to support drug discovery for patients with lung cancer, patients were divided into 3 groups based on the severity of the disease. Smoking and alcohol consumption habits were recorded for all 3 groups. Is this an example of an observational study or experimental study? The study is an experiment. The controlled factor is the smoking and alcohol consumption habits. The study is an experiment. The controlled factor is the severity of the disease. The study is an observational study. The study is an experiment. The controlled factor is whether or not the person has lung cancer.

The study is an observational study. The samples are chosen using an appropriate process; however, no attempt is made to control any aspect of the individuals in the sample, even though the variables of interest are recorded for each group.

In a study to add a new feature to a software program, the programmer introduced two categories, men and women, in the survey she conducted. Is the study observational or experimental? If it is an experiment, what is the controlled factor? The study is an experiment. The controlled factor is the feature to be added in the software. The study is an experiment. The controlled factor is the category, men or women. The study is an observational study. The study is an experiment. The controlled factor is the survey.

The study is an observational study. The samples are chosen using an appropriate process; however, no attempt is made to control any aspect of the sample even though the variables of interest are recorded for each group.

A study was conducted to determine whether a new highway should be built next to the river in a town. Half of the residents in the town live near the river. The sample of this study consisted of all the residents in the town who live near the river. Which of the following describes the sampling of this study?

There is sampling bias. Sampling bias exists in this study because the people who live near the river probably have stronger opinions about a new highway being placed next to their homes than the rest of the residents in the town who do not live close to the river.

Select all of the following scenarios below that contain nonbiased samples. To estimate the political party distribution of residents in his state, Frank collects data from a large group of randomly selected residents of his city. To estimate the mean number of classes that students take at his university, Samuel collects data from a randomly selected proportionate number of students from each grade level. David wants to estimate the mean grade point average of students at his school. He collects data by recording the grade point average of every 25th student on the list of students after a randomly selected first student. Helen wants to estimate the male to female ratio of the residents of her city. She collects data by recording the sex of every 50th resident after selecting a random starting point on a list of residents.

To estimate the mean number of classes that students take at his university, Samuel collects data from a randomly selected proportionate number of students from each grade level. David wants to estimate the mean grade point average of students at his school. He collects data by recording the grade point average of every 25th student on the list of students after a randomly selected first student. Helen wants to estimate the male to female ratio of the residents of her city. She collects data by recording the sex of every 50th resident after selecting a random starting point on a list of residents. A sample is biased if some individuals of the population are more or less likely to be selected than others. The sample from choice B is nonbiased because every student has an equal chance of being selected. The sample from choice C is nonbiased because every student has an equal chance of being selected. The sample from choice D is nonbiased because every resident has an equal chance of being selected.

Which of the following scenarios contain biased samples? Select all that apply. To estimate which presidential candidate is likely to win the vote of a town, Mark collects data by interviewing people leaving a local Christian church. Kenneth wants to estimate the mean height of students at his school. He collects data by selecting a random group of students within his classroom. To estimate the male to female ratio of the residents of her city, Janice collects data by recording the sex of every 50th resident after selecting a random starting point on a list of residents. Amy wants to estimate the mean grade point average of students at her school. She collects data by recording the grade point average of every 25th student on the list of students after a randomly selected first student.

To estimate which presidential candidate is likely to win the vote of a town, Mark collects data by interviewing people leaving a local Christian church. Kenneth wants to estimate the mean height of students at his school. He collects data by selecting a random group of students within his classroom. A sample is biased if some individuals of the population are more or less likely to be selected than others. The sample from choice A is biased because members of the Christian church are likely to have different political views than the rest of the population. The sample from choice B is biased because the students in this classroom may only represent one grade level, which could be shorter or taller in general than other grade levels.

True or False? In reference to different sampling methods, cluster sampling includes the steps: use simple random sampling to select a set of groups; every individual in the chosen groups is included in the sample.

True It is true that cluster sampling includes the steps: use simple random sampling to select a set of groups; every individual in the chosen groups is included in the sample.

True or false? Discrete is the type of quantitative data that is the result of counting.

True; Discrete is defined as the type of quantitative data that is the result of counting.

A researcher is interested in the effects of watching videos just before bed on the quality of sleep. Which of the following claims would be appropriate for this situation? Select only one answer choice. Watching videos just before bed reduces quality of sleep. More than 60% of people watch videos just before going to bed. Watching 1 hour of video just before going to bed reduces the number of minutes of REM sleep by more than 10%. Watching 1 hour of video just before going to bed reduces the quality of sleep.

Watching 1 hour of video just before going to bed reduces the number of minutes of REM sleep by more than 10%. The claim or question needs to be testable in order to be analyzed using a statistical process. By using a specified number of hours of video and making a quantitative claim about the effect on REM sleep, the claim can be tested using an appropriate data set.

A consumer research company is interested in determining if a certain company's new refrigerator model is more efficient than the older model. What should the researchers do first? Write a claim about the efficiency of the new model that can be tested. Choose a random sample of the new models to perform testing. Make some initial conclusions about the efficiency of the new model. Make some initial conclusions about the efficiency of the old model.

Write a claim about the efficiency of the new model that can be tested. The researchers are at the starting point of the process. They first need to create a question or claim that is testable.

A candy manufacturer is interested in the distribution of colors in each of its packages of candy sold. What should the researchers do first? Write a question about the distribution of colors in each package. Choose a random sample of candy packages to analyze. Make some initial conclusions about the distribution of the colors. Make some initial conclusions about the colors most people want.

Write a question about the distribution of colors in each package. The researchers are at the starting point of the process. They first need to create a question or claim that is testable.

There are more people who volunteer in soup kitchens in the state of California than in the state of Arizona. Therefore, the people of the state of California are more willing to volunteer their time than the people of Arizona. Is there a problem with this logic? Explain. Yes, there is a problem with the logic. More people in California live by a beach, and are therefore more willing to volunteer than those people in Arizona. Yes, there is a problem with the logic. California has more residents than Arizona, therefore there is a likelihood that there will be more volunteers in soup kitchens as well. No, there is not a problem with the logic. The number of volunteers in California is greater than in Arizona, which means that people in California are more likely to volunteer in soup kitchens than people in Arizona. No, there is not a problem with the logic. There are more soup kitchens in the state of California, so there will be more volunteers.

Yes, there is a problem with the logic. California has more residents than Arizona, therefore there is a likelihood that there will be more volunteers in soup kitchens as well. The flat number of volunteers is likely proportional to the number of residents a state has. California is a larger state than Arizona and contains more people, so it is highly likely that it will also have more volunteers. However, in general, this does not mean that all people in the state of California are more willing to volunteer than those in Arizona.

What is the type of quantitative data that is the result of measuring? qualitative statistic discrete continuous

continuous Continuous is defined as the type of quantitative data that is the result of measuring.

What is the type of quantitative data that is the result of measuring? qualitative statistic discrete continuous

continuous is defined as the type of quantitative data that is the result of measuring.

Given that Angelina is collecting data on commute distance, what type of data is she working with? qualitative discrete quantitative continuous quantitative none of the above

continuous quantitative Commute distance is continuous quantitative data because it is obtained by measuring and is not limited to a certain set of numbers.

Given that Justin is collecting data on reaction time, what type of data is he working with? qualitative discrete quantitative continuous quantitative none of the above

continuous quantitative Reaction time is continuous quantitative data because it is obtained by measuring and is not limited to a certain set of numbers.

Given that Justin is collecting data on reaction time, what type of data is he working with? qualitative discrete quantitative continuous quantitative none of the above

continuous quantitative Reaction time is continuous quantitative data because it is obtained by measuring and is not limited to a certain set of numbers.

Patrick is collecting data on shoe sizes available at a shoe store. What type of data is this? qualitative discrete quantitative continuous quantitative none of the above

discrete quantitative Shoe size is discrete quantitative data because it only takes on certain values, such as 5, 5.5, 6, 6.5, etc.

When considering different sampling methods, stratified sampling includes the steps: _______. divide the population into groups; use simple random sampling to identify a proportionate number of individuals from each group list the members of the population; use simple random sampling to select a starting point in the population; let k = (number of individuals in the population)/(number of individuals needed in the sample); choose every kth individual in the list starting with the one that was randomly selected identify individuals of the population that are easily accessible; obtain data from these individuals use simple random sampling to select a set of groups; every individual in the chosen groups is included in the sample

divide the population into groups; use simple random sampling to identify a proportionate number of individuals from each group Stratified sampling includes the steps: divide the population into groups; use simple random sampling to identify a proportionate number of individuals from each group.

Michelle is investigating if gender has any effect on political party associations. What is the explanatory variable? political party associations gender the number of people that are being studied none of the above To determine whether or not number of siblings influences grade point average, Charles has designed a survey. What is the explanatory variable? number of siblings grade point average the number of people surveyed none of the above

gender The explanatory variable is the independent variable, which is the variable that is changed to determine its effect on a dependent variable. In this case the explanatory variable is gender.

Janice is investigating if grade level has any effect on time spent studying. What is the explanatory variable? time spent studying grade level the number of people that are being studied none of the above

grade level The explanatory variable is the independent variable, which is the variable that is changed to determine its effect on a dependent variable. In this case the explanatory variable is grade level.

When considering different sampling methods, systematic sampling includes the steps: _______. list the members of the population; use simple random sampling to select a starting point in the population; let k = (number of individuals in the population)/(number of individuals needed in the sample); choose every kth individual in the list starting with the one that was randomly selected use simple random sampling to select a set of groups; every individual in the chosen groups is included in the sample identify individuals of the population that are easily accessible; obtain data from these individuals divide the population into groups; use simple random sampling to identify a proportionate number of individuals from each group

list the members of the population; use simple random sampling to select a starting point in the population; let k = (number of individuals in the population)/(number of individuals needed in the sample); choose every kth individual in the list starting with the one that was randomly selected Systematic sampling includes the steps: list the members of the population; use simple random sampling to select a starting point in the population; let k = (number of individuals in the population)/(number of individuals needed in the sample); choose every kth individual in the list starting with the one that was randomly selected.

Given that Janet is collecting data on favorite sports teams, what type of data is she working with? Given that Ruth is collecting data on political party preference, what type of data is she working with? qualitative discrete quantitative continuous quantitative none of the above

qualitative Favorite sports teams + political party preferences are qualitative data because it involves categorization of non-numerical attributes.

Rebecca is investigating if height has any effect on red blood cell count. What is the response variable? height the number of people that are being studied red blood cell count none of the above

red blood cell count The response variable is the dependent variable, which is the variable that is being measured or tested in response to changes in the independent variable. In this case the response variable is red blood cell count.

Which of the following is the situation in which not all members of the population are equally likely to be selected? sampling error sampling bias nonsampling error random sampling

sampling bias A sampling bias is defined as the situation in which not all members of the population are equally likely to be selected.

Which of the following best describes the term response variable? the independent variable in an experiment a variable that has an effect on a study even though it is neither an independent nor a dependent variable the dependent variable in an experiment a value or component of the independent variable applied in an experiment

the dependent variable in an experiment A response variable is defined as the dependent variable in an experiment.

Which of the following best describes the term explanatory variable? the dependent variable in an experiment a value or component of the independent variable applied in an experiment a variable that has an effect on a study even though it is neither an independent nor a dependent variable the independent variable in an experiment

the independent variable in an experiment An explanatory variable is defined as the independent variable in an experiment.

Timothy wants to estimate the percentage of homeowners that own at least one dog. He surveys 100 randomly selected homeowners to determine whether or not they own dogs. What is the parameter? all homeowners specific responses to the survey the percentage of all homeowners that own at least one dog the 100 homeowners surveyed the percentage of surveyed homeowners that own at least one dog

the percentage of all homeowners that own at least one dog A parameter is a number that is used to represent a population characteristic. In this case, the parameter is the percentage of all homeowners that own at least one dog.

Patrick wants to estimate the percentage of parents that use cloth diapers. He asks a randomly selected group of 125 parents whether or not they use cloth diapers. What is the statistic? the 125 people surveyed the percentage of all parents that use cloth diapers the percentage of surveyed parents that use cloth diapers all parents that use cloth diapers specific "yes" or "no" responses to the survey

the percentage of surveyed parents that use cloth diapers A statistic is a numerical characteristic of the sample. In this case, the statistic is the percentage of surveyed parents that use cloth diapers. FEEDBACK