STATS FINAL
For the situation shown below, what is the appropriate interpretation of the statistical results? A weight-lifting coach claims that weight-lifters can increase their strength by taking a certain supplement. To find out, he does an experiment and performs a dependent two-sample t-test. The statistical results are below. Alpha:0.10 Critical Value:+2.228 Test Statistic:+4.17 p-Value:0.001 The coach is not correct. The supplement did not increase the athlete's strength. These statistical results are not conclusive because the critical value should have been +/-. The coach is not correct, because you do not reject H(0) when p-value is less than alpha. The coach is correct. The supplement did increase the athlete's strength.
The coach is correct. The supplement did increase the athlete's strength.
What information does the null hypothesis express? The researcher's believed value of the population mean. A mathematical interval for the population mean. The preferred outcome of the hypothesis test. The currently believed value of the population mean.
The currently believed value of the population mean.
Please choose the location and spread for the t-equation for an independent two-sample situation. The two spreads combined together(√s21n1+s22n2). The two spreads added together (S1√n1+s2√n2) The location of the column of differences ((¯x1−x2)). The difference in the two locations ¯x1−¯x2
The difference in the two locations ¯x1−¯x2 The two spreads combined together(√s21n1+s22n2).
What is the magnitude (ignore mathematical sign) of the critical value for a left-tailed hypothesis test, with: α=0.10 n=13 s=11.93 Critical value = 1.782. Critical value = 1.350. Critical value = 1.64. Critical value = 1.356.
Critical value = 1.356.
What is the magnitude (ignore mathematical sign) of the critical value for a right-tailed hypothesis test, with: α=0.05 n=15 s=4.00 Critical value = 2.145. Critical value = 2.131 Critical value = 1.96. Critical value = 1.761.
Critical value = 1.761.
What is the magnitude (ignore mathematical sign) of the critical value for a two-tailed hypothesis test, with: α=0.01 n=20 s=1.35 Critical value = 2.845. Critical value = 2.861. Critical value = 2.539. Critical value = 2.580.
Critical value = 2.861.
Click the two conclusions possible in Step 3: Infer of the General Method to solve problems in statistics. Select Answer(s) Do REJECT the null hypothesis. Do NOT REJECT the null hypothesis. Do REJECT the alternative hypothesis. Do NOT REJECT the alternative hypothesis.
Do REJECT the null hypothesis. Do NOT REJECT the null hypothesis.
What is the proper conclusion to a hypothesis test using the information below: H0:μ=148 H1:μ<148 α=005 p−value=0.15 Do reject the null hypothesis because p-value is larger than alpha. Do not reject the null hypothesis because p-value is larger than alpha. Not enough information is given to make a conclusion. Do reject the null hypothesis because p-value does not equal alpha.
Do not reject the null hypothesis because p-value is larger than alpha.
What is the proper conclusion to a hypothesis test using the information below: H0:μ=148 H1:μ≠148 Critical value = +/- 2.032 Test statistic =-1.478 Do not reject the null hypothesis because the test statistic is in the acceptance region. Do not reject the alternative hypothesis because the test statistic is in the acceptance region. Do reject the null hypothesis because the test statistic is in the rejection region. Do reject the null hypothesis because the test statistic is less than zero (0).
Do not reject the null hypothesis because the test statistic is in the acceptance region.
What is the proper conclusion to a hypothesis test using the information below: H0:μ=148 H1:μ<148 α=005 p−value=0.0005 Do not reject the null hypothesis because p-value is less than alpha. A critical value and a test statistic is needed to make a conclusion in a hypothesis test. Do reject the null hypothesis because p-value is less than alpha. Do reject the null hypothesis because p-value does not equal alpha.
Do reject the null hypothesis because p-value is less than alpha.
What is the proper conclusion to a hypothesis test using the information below: H0:μ=148 H1:μ<148 Critical value = -1.753 Test statistic = -3.478 Do not reject the alternative hypothesis because the test statistic is in the rejection region. Do not reject the null hypothesis because the test statistic is in the acceptance region. Do reject the null hypothesis because the test statistic is less than zero (0). Do reject the null hypothesis because the test statistic is in the rejection region.
Do reject the null hypothesis because the test statistic is in the rejection region.
T/F A statistically significant result always means a practically significant result to be followed in practice.
False
Where does the value of a test statistic come from? From converting the sample average into a z-score, or t-value. From the result of a hypothesis test. From the researchers point of interest. From the z-table, or t-table.
From converting the sample average into a z-score, or t-value.
In hypothesis testing, where does the hypothesized value NOT come from? From the researcher's educated opinion. From the results of prior research. From an expert in the field of study. From the results of the sample.
From the results of the sample.
Where does the value of the test statistic come from? From the t-equation t0=¯x−μs√n. From the t-table (t0=2.359). From the confidence interval (CI%=¯¯¯¯χ±t(s√n)). From a previously known value of the population mean.
From the t-equation t0=¯x−μs√n.
Click all choices that are steps in Step A: Abstract of the General Method to solve problems in statistics. Find the critical value from probability. Get descriptive statistics from the sample data values. Write a set of two hypotheses about the researcher's question. Calculate the test statistic from the sample information.
Get descriptive statistics from the sample data values. Write a set of two hypotheses about the researcher's question.
Please match each region below with the appropriate area under a schematic normal curve. A. The acceptance region B. The rejection region. The body area of the schematic normal curve. One, or both, tail area(s) of the schematic normal curve.
The body area of the schematic normal curve. : A. The acceptance region One, or both, tail area(s) of the schematic normal curve. : B. The rejection region.
What information does the alternative hypothesis express? The currently believed value of the population mean. The researcher's believed value of the population mean. A mathematical interval for the population mean. The preferred outcome of the hypothesis test.
The researcher's believed value of the population mean.
For the situation below, what is the appropriate interpretation of the statistical results? A forester was responsible for growing pine trees as fast as possible to supply a local paper mill. He wondered if it made a difference whether the tree was planted just to the south, or just to the north, of another\n pine tree. After his experiment, he ran an independent two-sample t-test and got the statistical results below. Alpha:0.10 Critical Value:+1.315 Test Statistic:+3.067 p-Value:0.0025 The trees planted just to the south grew the same as the trees planted to just to the north. The trees planted just to the south did grow faster than the trees planted to just to the north. The trees planted just to the south grew 3.067/1.315 = 2.33 times faster than the trees planted to just to the north. The difference in growth rate as 0.0025, which means both trees grew the same amount.
The trees planted just to the south did grow faster than the trees planted to just to the north.
For a dependent two-sample situation, what is the appropriate degrees of freedom? The usual degrees of freedom (nd−1). Satterthwaite's approximate degrees of freedom (given in the problem). Dependent degrees of freedom ((n1−1)−(n2−1)(n1−1)+(n2−1)). Pooled degrees of freedom ((n1−1+(n2−1)).
The usual degrees of freedom (nd−1).
What are the two most significant ways that two-sample situations differ from one-sample situations? The two locations can be the same or different. There are twice as many sources of variation in the situation. The two spreads can be the same or different. Step A: Abstract is much more difficult.
There are twice as many sources of variation in the situation. The two spreads can be the same or different.
Does the value in the null hypothesis always equal zero (0)? Yes, because the mean of all difference always equals zero. Yes, because that indicates the two population means are equal. No, because the difference between two numbers can be a positive or negative number. No, the value in the null hypothesis is decided by the researcher.
Yes, because that indicates the two population means are equal.
For an independent two-sample situation, does it matter how the difference is calculated? No, an independent two-sample t-test is always a two-tail situation. Yes, it must always be the greater value minus the lesser value. No, for a one-tail situation, and Yes for a two-tail situation. Yes, for a one-tail situation, and No for a two-tail situation.
Yes, for a one-tail situation, and No for a two-tail situation.
For a dependent two-sample situation, does it matter how the difference is calculated? No, because the dependent two-sample t-test can handle either difference. No, because more than one alternative hypothesis can be written. Yes, it must be the greater value minus the lesser value to always give a positive difference. Yes, in a one-tail situation the difference determines the direction of the inequality sign in the alternative hypothesis.
Yes, in a one-tail situation the difference determines the direction of the inequality sign in the alternative hypothesis.
For a dependent two-sample situation, what is the main consequence after choosing how the difference is calculated? The sign of the difference values is then fixed. This choice determines the question that is asked in this situation. You must use the same difference through all calculations in the method. Yes, it determines how the difference should be entered into a calculator.
You must use the same difference through all calculations in the method.
Click which choice is NOT a descriptive statistic. t0 n x bar S
t0
What is the appropriate equation for an independent two-sample t-test. t0=¯d−0sd√n t0=¯d−0sd(n−1) t0=(¯x1−¯x2)−0√s1n21+s2n22 t0=(¯x1−¯x2)−0√s1n21+s2n22
t0=(¯x1−¯x2)−0√s1n21+s2n22
What is the value of the test statistic for a right-tail hypothesis test using the information below: μ=8.0 α=0.05 n=25::¯x=8.9::s=1.8 t0=−5.83 t0=+1.10 t0=+2.50 t0=+2.73
t0=+2.50
What is the appropriate equation for a dependent two-sample t-test. t0=¯d−0sd√n t0=(¯x1s1+¯¯¯x2s2)2(n1−1)+(n2−1) t0=¯d−0sd(n−1) t0=(¯x1−¯x2)−0√s1n21+s2n22
t0=¯d−0sd√n
What is the value of the test statistic for a two-tail hypothesis test using the information below: μ=8.0 α=0.02 n=15::¯x=7.3::s=1.8 t0=−1.51 t=+1.10 t0=−2.73 t0=−5.83
t0=−1.51
Click which choice below is NOT an appropriate rejection region. A right tail area. A left tail area. A two tail area. A middle body area.
A middle body area.
Please match the following inequalities, and equality, to their meaning in a distribution. A. Greater than B. Less than C. Not equal to A one-tail to the left situation. A one-tail to the right situation. A two-tail situation.
A one-tail to the left situation. : B. Less than A one-tail to the right situation. : A. Greater than A two-tail situation. : C. Not equal to
How is a conclusion made in the Levene's equality of variance test? A p-value greater than 0.05 means that the two population variances are not equal. A p-value less than 0.05 means that the two population variances are not equal. Finding the Levene's p-value in the Levene's table tells if the two population variances are equal, or not. A Levene's p-value greater than 1.00 means that the two population variances are equal.
A p-value less than 0.05 means that the two population variances are not equal.
Select all choices that are appropriate for a dependent two-sample situation. A random sample from one population and a matched sample from another population. A random sample from one population and a random sample from another population. A random sample of pairs of individuals. A random sample of individuals divided into two groups.
A random sample from one population and a matched sample from another population. A random sample of pairs of individuals.
Select all choices that are appropriate for an independent two-sample situation. A random sample from one population and a random sample from another population. A random sample from one population and a matched sample from another population. A random sample of pairs of individuals. A random sample of individuals divided into two groups.
A random sample from one population and a random sample from another population. A random sample of individuals divided into two groups.
Please match each alternative hypothesis below with the appropriate statistical situation. A. H1:μ<0 B. H1:μ>0 C. H1:μ≠0 A two-tail situation means the critical value is positive and negative. A right-tail situation means the critical value is positive. A left-tail situation means the critical value is negative.
A two-tail situation means the critical value is positive and negative. : C. H1:μ≠0 A right-tail situation means the critical value is positive. : B. H1:μ>0 A left-tail situation means the critical value is negative. : A. H1:μ<0
Use the information below to match the following statistics with their appropriate value. An owner of a small company in interested in a new computer training program for employees, but she wants to make sure that it is effective in her company before purchasing it. She directs you to find out, so you randomly select 10 employees and measure their improvement in score by giving them a test both before and after the program. Then the difference is calculated and recorded, finding an average difference of 2.6 with a standard deviation difference of 2.93. Please perform a hypothesis test at a 0.10 level of significance to find out. A. The conclusion B. The p-value C. The value of the test statistic +2.81 0.01 Do reject H(0) - there is an improvement in scores.
A. The conclusion: Do reject H(0) - there is an improvement in scores. B. The p-value: 0.01 C. The value of the test statistic: +2.81
Use the information below to match the following statistics with their appropriate value . Your boss in the human resources department at a local company asks you to find out if the employee's monthly allowances need to be raised because of inflation. Employee monthly allowances are now set at $500 per month. To answer this question with evidence, you randomly select 40 employees and measure how much they spend each month, finding an average of $640 and a standard deviation of $250. Please perform a hypothesis test at a 0.05 level of significance to find out. A. The p-value B. The value of the test statistic C. employee's allowances have gone up. +3.54 0.0005 Do reject H(0) - employee's allowances have gone up.
A. The p-value: 0.0005 B. The value of the test statistic: +3.54 C. employee's allowances have gone up. : Do reject H(0) - employee's allowances have gone up.
Use the information below to match the following statistics with their appropriate value . A measure of how hard is a material is the Brinell scale. An engineer does not believe that the hardness of a new metal alloy he invented is equal to a Brinell score of 170. To find out, he took 25 pieces of the new alloy and measured their hardness, finding an average score of 174.52 and a standard deviation score of 10.31. Please perform a hypothesis test at a 0.01 level of significance to find out. Hit Spacebar to access and hit Enter to open. A. The p-value B. The conclusion C. The value of the test statistic +2.19 0.04 Do not reject H(0) - the engineer's claim is not correct.
A. The p-value: 0.04 B. The conclusion: Do not reject H(0) - the engineer's claim is not correct. C. The value of the test statistic: +2.19
Use the information below to match the following statistics with their appropriate value. A local company making batteries for electric bicycles claim that their batteries have a mean lifetime of 2.1 years under normal use. A local store renting electric bicycles decided to find out if these batteries had a different lifetime. The store randomly chose 10 bicycles and measured the time it took for the batteries to fail, finding an average lifetime of 2.14 years with a standard deviation of 0.18 years. Please perform a hypothesis test at a 0.05 level of significance to find out. A. The p-value B. The value of the test statistic C. The conclusion +0.70 0.500 Do not reject H(0) - the store's claim is not correct.
A. The p-value: 0.500 B. The value of the test statistic: +0.70 C. The conclusion: Do not reject H(0) - the store's claim is not correct.
Use the information below to match the following statistics with their appropriate value . An instructor teaches a large statistics course at a local university and wonders how this semester's students are doing. She knows that in prior semesters students had a mean score of 75 on the final exam, and she doesn't think that this semester's students will score the same. To find out, she randomly selects 31 students and measures this semester's final exam score. She finds an average score of 77 and a standard deviation score of 16.54. Please perform a hypothesis test at a 0.01 level of significance to find out. A. The value of the test statistic B. Do not reject H(0) - students did score the same as before. C. The p-value +0.67 0.50 Do not reject H(0) - students did score the same as before.
A. The value of the test statistic: +0.67 B. Do not reject H(0) - students did score the same as before. : Do not reject H(0) - students did score the same as before. C. The p-value : 0.50
Use the information below to match the following statistics with their appropriate value . There is prior evidence that lawn mower engines will run for a mean of 240 minutes on a gallon of gasoline. An amateur inventor develops a new lawn mower engine that he claims will run for more than 240 minutes on a gallon of gasoline. To find out, a local consumer agency took 36 of the new engines and ran them each on a gallon of gasoline. They found a average run time of 249 minutes with a standard deviation of 41 minutes. Is the amateur inventor's claim correct? Please perform a hypothesis test at a 0.05 level of significance to find out. Hit Spacebar to access and hit Enter to open. Answer has been selected. A. The value of the test statistic B. The p-value C. The conclusion +1.32 0.10 Do not reject H(0) - the inventor's claim is not correct.
A. The value of the test statistic: +1.32 B. The p-value: 0.10 C. The conclusion: Do not reject H(0) - the inventor's claim is not correct.
Use the information below to match the following statistics with their appropriate value . A nutritionist believes that teenagers who don't eat fast food intake fewer calories each day. Earlier, the nutritionist had studied teenagers who do eat fast food and found they consumed a mean of 2,637 calories per day. To answer her question, the nutritionist then studied teenagers who do not eat fast food. She measured 61 teens for their calorie intake and found an average of 2,258 calories with a standard deviation of 1,519 calories. Please perform a hypothesis test at a 0.10 level of significance to find out. A. The value of the test statistic B. The conclusion C. The p-value -1.95 0.025 Do reject H(0) - the nutritionist's claim is correct.
A. The value of the test statistic: -1.95 B. The conclusion: Do reject H(0) - the nutritionist's claim is correct. C. The p-value: 0.025
Please match the following questions with their answers for the t-equation to convert a sample average into a standardized value t0=¯x−μs√n. A. What goes in the denominator? B. What goes in the numerator? The location of the sample average (adjusted for mu). The spread of the sample average.
A. What goes in the denominator? : The spread of the sample average. B. What goes in the numerator? : The location of the sample average (adjusted for mu).
In a hypothesis test, what is the size of the Type I error? Alpha (α). Beta (β). Gamma (χ). Delta (δ).
Alpha (α).
For a dependent two-sample situation, what is the value in the null hypothesis? Always zero (0). Positive if the difference is greater data value minus lesser data value. Negative if the difference is lesser data value minus greater data value. The null value only equals zero when the difference equals zero.
Always zero (0).
For an independent two-sample situation, what is the value in the null hypothesis? Always zero (0). Can be a positive or negative value. Zero (0) when the researcher's question is if the population means are different. Sometimes zero (0).
Always zero (0).
Select all choices that are appropriate for an independent two-sample situation. Any husband and any wife. Any husband and their wife. Any student tested before a semester and the same student tested after a semester. Any husband and any wife. Any student tested before a semester and any student tested after a semester.
Any husband and any wife. Any student tested before a semester and any student tested after a semester.
If Satterthwaite's degrees of freedom is given in the problem, why use it over Welch's degrees of freedom. Because Satterthwaite's is a newer approximation than Welch's. Because Satterthwaite's is a much more complicated approximation than Welch's. Because Satterthwaite's is a much, much better approximation than Welch's. Because Welch's approximation has fallen out of favor in the field of statistics.
Because Satterthwaite's is a much, much better approximation than Welch's.
Why does a dependent two-sample situation have two sources of variation? Because both s1 and s2 can vary from sample to sample. Because both ¯x1 and ¯x2can vary from sample to sample. Because both ¯d and sd can vary from sample to sample. Because the difference between ¯d and sd can vary from sample to sample.
Because both ¯d and sd can vary from sample to sample.
Why is the method of hypothesis testing called an inferential method of statistics? Because it uses similar mathematics to a confidence interval, which is an inferential method. Because it gives the best guess (infers) from the sample for the value of the population mean. Because it infers whether the researcher's belief is correct, or not. Because it infers the end result.
Because it gives the best guess (infers) from the sample for the value of the population mean.
Why is removing the dependency a reasonable option in a dependent one-sample situation? Because the dependency is a perception and is not real Because every other method was much more complicated and difficult to perform. Because adding dependency made a more complicated situation to understand and solve. Because it is both logically and mathematically correct and easy to do.
Because it is both logically and mathematically correct and easy to do.
For the situation below, what is the appropriate interpretation of the statistical results? Alpha:0.02 Critical Value:+2.398 Test Statistic:+1.833 p-Value:0.05 The two genders of children had different weights. The male gender weighed more than the female gender. Both genders of children were weighed. Both genders of children had the same weight.
Both genders of children had the same weight.
In hypothesis testing, how is close and far determined? By using a ruler on a schematic curve. By the mathematical distance between the sample average and the hypothesized mean. By converting the situation from the sample distribution into the z, or t, distribution. By comparing the sample average to its z-score, or t-value.
By converting the situation from the sample distribution into the z, or t, distribution.
In statistics, what is the advantage of pooling information? By pooling, two sample statistics can be combined into one population parameter. By pooling, two pieces of information about a population can be combined into one better piece of information. Pooling information is a way to reduce the numbers that must be accounted for. Pooling means comparing two pieces of information and selecting the better piece.
By pooling, two pieces of information about a population can be combined into one better piece of information.
How does the method of hypothesis testing make an inference (i.e. draw a conclusion) about a population mean? By seeing if the critical value is inside the confidence interval. By seeing if the test statistic is inside the critical region. By seeing if the value of the test statistic is less than zero (0). By seeing if the test statistic is closer to zero (0), or farther from zero, than the critical value.
By seeing if the test statistic is closer to zero (0), or farther from zero, than the critical value.
Click all choices that are steps in Step 2: Analyze of the General Method to solve problems in statistics. Find the critical value from probability information. Use the test statistic and the critical value to make a statistical inference. Calculate the test statistic from sample information. Find the p-value from the test statistic.
Calculate the test statistic from sample information. Find the p-value from the test statistic.
In hypothesis testing, what does reasonableness mean? How likely a reasonable person would agree with a chosen value. How reasonable the chosen value and the value of the population mean are different. How close a chosen value is to the population mean. How reasonable is the hypothesis about the value of the population mean.
How close a chosen value is to the population mean.
For the situation below, what is the appropriate interpretation of the statistical results? A study was conducted to find out if the salaries of elementary school teachers were equal to high school teachers. The researcher performed a dependent two-sample t-test and the statistical results are shown below. Alpha:0.05 Critical Value:-1.729 Test Statistic:-0.853 p-Value:0.40 Income for teachers at the two schools was equal. Income for teachers at the two schools was not equal. Income for teachers at the two schools was way too low. Income for teachers at the two schools was not equal because the sample averages were not equal.
Income for teachers at the two schools was equal.
What statistical method is used to tell if two population variances are equal, or not equal? Satterthwaite's Equality of Variance Test. Tukey's Equality of Variance Test. Levene's Equality of Variance Test. Visible observation by just looking at the two variances.
Levene's Equality of Variance Test.
How is Levene's equality of variance test to be interpreted? Levene's is a hypothesis test best interpreted using the p-value approach. Levene's is a confidence interval best interpreted using the mu-in-the-barn method. Levene's can best be interpreted using a Levene's table. Levene's is best interpreted using a Schematic Curve for the Levene's distribution.
Levene's is a hypothesis test best interpreted using the p-value approach.
For an independent two-sample situation, select the choice that expresses the statistical logic used to work with two samples of independent information. Treat the information as a random selection of pairs. Must treat the information in each sample separately. Statistically analyze the differences between pairs of data values. Statistically analyze the individual data values.
Must treat the information in each sample separately. Statistically analyze the differences between pairs of data values.
Use the information below... There is prior evidence that lawn mower engines will run for a mean of 300 minutes on a gallon of gasoline. An amateur inventor develops a new lawn mower engine that he claims will run for more than 300 minutes on a gallon of gasoline. To find out, a local consumer agency took 51 of the new engines and ran them each on a gallon of gasoline. They found a average run time of 305 minutes with a standard deviation of 30 minutes Is the amateur inventor's claim correct? No, the amateur inventor's claim is not correct, because the test statistic = 1.19 and the critical value = 1.676. Yes, the amateur inventor's claim is correct, because the test statistic is in the acceptance region of the schematic curve. No, the amateur inventor's claim is not correct, because the test statistic is less than zero (0). Yes, the amateur inventor's claim is correct, because the p-value is greater than alpha (α)
No, the amateur inventor's claim is not correct, because the test statistic = 1.19 and the critical value = 1.676.
For a dependent two-sample situation, does it matter how the difference is calculated? Not for doing the calculations; but Yes, for interpreting the results. Yes, because positive numbers are easier to work with. No, because computers can always change the mathematical sign to whatever is needed. Yes, because it makes a difference in how it should be entered into a calculator.
Not for doing the calculations; but Yes, for interpreting the results.
For an independent two-sample situation, select the two most appropriate degrees of freedom? Pooled degrees of freedom((n1−1)+(n2−1)),when the population variances are considered equal. Satterthwaite's approximate degrees of freedom (given in the problem), when the population variances are considered not equal. Independent degrees of freedom ((n1−1)−(n2−1)(n1−1)+(n2−1)), when the population variances are considered not equal. The usual degrees of freedom (nd−1),when the population variances are considered equal.
Pooled degrees of freedom((n1−1)+(n2−1)),when the population variances are considered equal. Satterthwaite's approximate degrees of freedom (given in the problem), when the population variances are considered not equal.
For an independent two-sample situation, what is the appropriate degrees of freedom with the information below? Levene's p-value:0.10 Pooled df:14 Satterthwaite's df:13.563 Pooled df = 14. Satterthwaite's df = 13. Cumulative df = 14 + 13 = 27. Levene's df = 0.01.
Pooled df = 14.
What logic is used in statistics to make it possible to test for the population mean in a dependent two-sample situation? Remove the dependency by subtracting the two data values to convert it to a one-sample situation. Remove the dependency by adding the two data values to convert it to a one-sample situation. Ignore the dependency and use caution in the interpretation of the results. Remove the dependency by changing the sampling design and repeating the experiment.
Remove the dependency by subtracting the two data values to convert it to a one-sample situation.
For a dependent two-sample situation, how is the dependency between data values handled? Combine the dependencies by addition to get one number for each pair of individuals. Changing the question asked to prevent any dependency. Averaging the dependencies to get a representative value. Remove the dependency by subtraction to get one number for each pair of individuals.
Remove the dependency by subtraction to get one number for each pair of individuals.
Click all choices that are the definition of p-value. The t-value of the test statistic. The area in one (or two) tail(s) from the value of the critical value. The area in one (or two) tail(s) from the value of the test statistic. The area between the test statistic and the critical value.
The area in one (or two) tail(s) from the value of the test statistic.
What is the appropriate degrees of freedom to use for a independent two-sample situation where the variances are known to be not equal. Welch's approximate degrees of freedom if Satterthwaite's is given in the problem. Satterthwaite's approximate degrees of freedom if given in the problem. The pooled degrees of freedom. The unpooled degrees of freedom.
Satterthwaite's approximate degrees of freedom if given in the problem.
For an independent two-sample situation, what is the appropriate degrees of freedom with the information below? Levene's p-value:0.01 Pooled df:98 Satterthwaite's df: 89.783 Pooled df = 98. Satterthwaite's df = 89. Difference df = 98 - 89 = 9. Neither df is appropriate.
Satterthwaite's df = 89.
Click all choices that are steps in the General Method to solve problems in statistics. Step A: Abstract - Relevant information from the question. Step 1: Theorize - Probability information from theory. Step 2: Analyze - Sample information from the abstraction step. Step 3: Infer - Population information from the analyze step.
Step A: Abstract - Relevant information from the question. Step 1: Theorize - Probability information from theory. Step 2: Analyze - Sample information from the abstraction step. Step 3: Infer - Population information from the analyze step. (ALL)
What does Reject the Null Hypothesis mean? That the null hypothesis is closer to the truth. That the null hypothesis is improperly written. That the researcher prefers the alternative hypothesis. That the alternative hypothesis is closer to the truth.
That the alternative hypothesis is closer to the truth.
In a hypothesis test, click the possible approaches that can be used to make a conclusion in Step 3: Infer. The Critical Value approach. The Test Statistic approach. The p-Value approach. The Confidence Interval approach.
The Critical Value approach. The p-Value approach. The Confidence Interval approach.
Using the method to Determine Sample Dependency, select the choice that is appropriate for a dependent two-sample situation. The answer to the method question is Matching. The answer to the method question is Random. The answer to the method question is The Same. The answer to the method question is Different.
The answer to the method question is Matching.
Using the method to Determine Sample Dependency, select the choice that is appropriate for an independent two-sample situation. The answer to the method question is Matching. The answer to the method question is Random. The answer to the method question is The Same. The answer to the method question is Different.
The answer to the method question is Random.
Click the two assumptions needed for the method of hypothesis testing. The sample size is greater than 30 data values. The data values are normally distributed. The individuals were randomly selected. The sample average is normally distributed.
The individuals were randomly selected. The sample average is normally distributed.
Please match each situation below with the information that goes in the middle of the schematic curve. A. Find probability B. Do a hypothesis test C. Find a confidence interval The known value of the population mean. The value of the sample average. The hypothesized value of the population mean.
The known value of the population mean. : A. Find probability The value of the sample average. : C. Find a confidence interval The hypothesized value of the population mean. : B. Do a hypothesis test
Please choose the location and spread for the t-equation for a dependent two-sample situation. Select Answer(s) The location of the difference column ¯¯¯d−0. The location of the sample average(¯¯¯x−μ) The spread of the difference column sd√η The spread of the sample average s√η.
The location of the difference column ¯¯¯d−0. The spread of the difference column sd√η.
What is the appropriate degrees of freedom to use for an independent two-sample situation where the variances are known to be equal. Welch's approximate degrees of freedom. Satterthwaite's approximate degrees of freedom. The pooled degrees of freedom. The unpooled degrees of freedom.
The pooled degrees of freedom.
In hypothesis testing, what does less than, or greater than, mean? The population mean could have a value of -∞ , and +∞. The population mean could have a value of -∞ , or +∞. The population mean could have a value of zero (0). The population mean could have a value.
The population mean could have a value of -∞ , or +∞.
Use the information below to determine the dependency of the situation. A nutritionist questions whether two soft drinks have the same effect on weight gain in teenagers who consume a lot of soft drinks. To find out, she randomly selects 50 teenagers and asks them to drink only soft drink #1 for six weeks. She then measures the change in weight for each teenager. Next, she asks the same teenagers to drink only soft drink #2 for six weeks, and measures the change in weight for each teenager. Use the information below to determine the dependency of the situation. This is an independent two-sample situation between teenagers drinking soft drinks. This is a dependent two-sample situation between teenagers drinking soft drinks. This situation is dependent on the teenagers drinking a lot of soft drink. This situation is independent of what the teenager's parents think.
This is a dependent two-sample situation between teenagers drinking soft drinks.
Use the information below to determine the dependency of the situation. An instructor teaches a large statistics course at a local university and wonders how this semester's students will do. Before the semester starts, she randomly samples 50 of her students and gives them a pretest. After the semester is over, she gives the same students a post test. She calculates the difference in scores to see how well her students did that semester. This is an independent two-sample situation. This is a dependent two-sample situation. This is a one-sample situation. This is a quasi-dependent two-sample situation.
This is a dependent two-sample situation.
Use the information below to determine the dependency of the situation. A researcher in marital relationships wants to study the difference in opinion between husbands and wives. To get information on this issue she randomly selects 50 husbands and randomly selects 50 wives. She then gives them a survey of questions designed to answer her question. Use the information below to determine the dependency of the situation. This is a dependent two-sample situation between husbands and wives. This is a relational-dependent between the husbands and the wives. This is a quasi-dependent two-sample situation between the husbands and the wives. This is an independent two-sample situation between husbands and wives.
This is an independent two-sample situation between husbands and wives.
Use the information below to determine the dependency of the situation. An instructor teaches a large statistics course at a local university and wonders how this semester's students will do. Before the semester starts, she randomly samples 50 of her students and gives them a pretest. After the semester is over, she randomly samples 50 other students and gives them a post test. She calculates the difference in scores to see how well her students did that semester. Use the information below to determine the dependency of the situation. This is an independent two-sample situation. This is a dependent two-sample situation. This is a rational dependent two-sample situation. This is a quasi-dependent two-sample situation.
This is an independent two-sample situation.
Click the two reasons that the method of hypothesis testing is needed. To find out how reasonable a chosen value is the population mean. To find out if it is reasonable to write a hypothesis about the value of the population mean. To find out if the population mean is less than, or greater than, a chosen value. To find out if a hypothesis about the value of the population mean makes sense.
To find out how reasonable a chosen value is the population mean. To find out if the population mean is less than, or greater than, a chosen value.
For a dependent two-sample situation, select all choices that express the statistical logic used to work with two samples of dependent information. Treat the information as a random selection of pairs. Treat the information as two groups of data values. Statistically analyze the differences between pairs of data values. Statistically analyze the individual data values.
Treat the information as a random selection of pairs. Statistically analyze the differences between pairs of data values.
T/F The Confidence Interval approach can only be used in a two-tail situation.
True
T/F The null hypothesis always contains an equal sign.
True
T/F The results of Levene's test is needed to properly interpret every independent two-sample t-test.
True
Click all choices that are steps in Step 1: Theorize of the General Method to solve problems in statistics. Use the schematic curve to analyze the situation from a statistical point of view. Find the appropriate critical value(s) for this situation. Use the critical value to find the appropriate probability. Calculate the test statistic to be able to make a statistical inference.
Use the schematic curve to analyze the situation from a statistical point of view. Find the appropriate critical value(s) for this situation.
For the situation below, what is the appropriate interpretation of the statistical results? A sugar maple grower long suspected that his trees produced more sugar maple syrup at night time, than during the day time. Having just retired, he ran an experiment and did a dependent two-sample t-test. The statistical results are shown below. Alpha:0.05 Critical Value:-1.697 Test Statistic:-1.700 p-Value:0.05 Using the p-value approach, it cannot be determined if the trees did produce differently at different times. These statistical results are weak and would be improved by getting more data values. Using the critical value approach, the trees did produce differently at different times. Though the evidence is weak. p-Value never equals alpha, so there must be an error in the calculations.
Using the critical value approach, the trees did produce differently at different times. Though the evidence is weak.
What is the p-value for a two-tail hypothesis test using the information below: μ=15 α=0.10 n=51::¯x=16.25::s=3.0 p-Value = 0.003. p-Value = 0.005. p-Value = 0.0025. p-Value = 0.010.
p-Value = 0.005.
What is the p-value for a right-tail hypothesis test using the information below: μ=65 α=0.05 n=23::¯x=70.6::s=12.3 p-Value = 0.01 . p-Value = 0.02 . p-Value = 0.04 . p-Value = 1.02
p-Value = 0.02 .
How is a pooled sample variance calculated? s2pooled=(n1−1)s21+(n2−1)s22(n1−1)+(n2−1) s2pooled=s21+s22(n1−1)+(n2−1) s2pooled=s21+s222 s2pooled=s21(n1−1)+s22(n2−1)
s2pooled=(n1−1)s21+(n2−1)s22(n1−1)+(n2−1)
