C 207 data driven pretest with ANSWERS checked

bayes' theorem

"trust theorem" = how much can you trust the evidence? Bayes can do magic! Ever wondered how computers learn about people? Example: An internet search for "movie automatic shoe laces" brings up "Back to the future" Has the search engine watched the movie? No, but it knows from lots of other searches what people are probably looking for. And it calculates that probability using Bayes' Theorem. Bayes' Theorem is a way of finding a probability when we know certain other probabilities. Example:dangerous fires are rare (1%)but smoke is fairly common (10%) due to barbecues,and 90% of dangerous fires make smoke We can then discover the probability of dangerous Fire when there is Smoke: P(Fire|Smoke) =P(Fire) P(Smoke|Fire)P(Smoke) =1% x 90%10% =9% So it is still worth checking out any smoke to be sure.

The number of customers that an automobile service shop receives on any given day is normally distributed with a mean of 75 and a standard deviation of 25. On a given day, 125 oil changes are performed. what is the probability on a given day of 125 or fewer oil changes? a. 97.5% b. 99% c. 67% d. 68.5%

*** 97.75 *** because 125 = 2 SD from the mean (75 + 25 + 25 = 125)

A manager of a call center is in charge of creating a staffing plan. The number of calls received per day is normally distributed. Which two statistics would be needed in order to estimate the number of calls that would be received 95% of the time? Choose 2 answers. a. Standard deviation b. Mean c. Median d. Interquartile range

*** Mean *** and Standard deviation (SD related to distance from the MEAN)

Analytics is a broad term that refers to a variety of tools that inform managerial decisions. Which term can be used to describe MANAGERIAL DECISIONS? Descriptive Prescriptive Pareto chart Biased

*** PRESCRIPTIVE ***

A research study examined the impact of product advertisement exposure on that product's brand awareness. The appropriate statistical test indicates that the null hypothesis should be rejected at the 5% significance level. What can be concluded from this study? the advertisement was effective in increasing sales? 95% of the subjects liked the brand? 5% of subjects did NOT like the brand? the advertisement was effective in building brand awareness?

*** the advertisement was effective in increasing sales ***

linear programming

***a mathematical technique that solves resource allocation problems*** a method for finding a minimum or maximum value of some quantity, given a set of constraints. Linear programming is used to obtain optimal solutions for operations research. Using linear programming allows researchers to find the best, most economical solution to a problem within all of its limitations, or constraints. Many fields use linear programming techniques to make their processes more efficient.

Given the following data set: 9 12 14 10 8 11 12 What is the mode? a. 8 b. 9 c. 11 d. 12

12b (it occurred twice, all other only once)

1 SDs from the mean

68% of values are less than one standard deviation (1SD) away from the mean value

2 SDs from the mean

95% of values are less than two standard deviations (2SD) away from the mean

3 SDs from the mean

99% of values are less than three standard deviations (3SD) away from the mean

Histogram

A graph of vertical bars representing the frequency distribution of a set of data.

run chart

A line cahrt that displays the history and pattern of variation of a process over time. or tool for tracking results over a period of time By collecting and charting data over time, you can find trends or patterns in the process. Because they do not use control limits, run charts cannot tell you if a process is stable. However, they can show you how the process is running.

Correlation

A measure of the extent to which two factors vary together, and thus of how well either factor predicts the other. Correlation. Correlation is a statistical technique that can show whether and how strongly pairs of variables are related. For example, height and weight are related; taller people tend to be heavier than shorter people. ... An intelligent correlation analysis can lead to a greater understanding of your data.

Control Variable (CV)

A variable that is kept the same (not changed) during the experiment.

response variable in a study

A variable that measures an outcome of a study. In statistics, a response variable, also known as a dependent variable, is a concept, idea, or quantity that someone wants to measure. It depends on an independent variable. A question is proposed, usually stating that the response variable will (or will not) change based on other factors.

a non profit organization ran an e-mail campaign with three different messages to solicit additional donations. what should the non profit organization use to determine if the average donation differs for the different messages? a. median b. mean c. ANOVA d. T-test

ANOVA

Heteroscedasticity

An unequal spread of Y scores around the regression line (that is around the values of Y'). In statistics, a collection of random variables is heteroscedastic if there are sub-populations that have different variabilities from others. Here "variability" could be quantified by the variance or any other measure of statistical dispersion. Thus heteroscedasticity is the absence of homoscedasticity.

In a statistical process control analysis, sample data are collected from an assembly line and measured to see if they fall within a tolerated measurement range. If an observation does fall within the range, a "yes" is recorded, and if it falls outside the range, a "no" is recorded.Which kind of data do the "yes" and "no" represent? a. Big datab. Biased datac. Variable datad. Attribute data

Attribute data

Attribute data vs. variable data

Attribute data are counted, variable data are measured.

A healthcare study follows a particular sample over time to identify how the health habits of teenagers impact their likelihood of acquiring various diseases later in their life in the hope that the healthcare organization will be able to create early prevention programs. Which type of research design does this study describe? a. Double blind study b. Systematic study c. Cohort study d. Experimental study

Cohort study

Which two (2) decision considerations describe fact-based decision making, according to the quality management principles? a. Decisions reduce external bias .b. Decisions have marginal effect on relationships with suppliers. c. Decisions foster trust in plans. d. Decisions use diversity of experience.

Decisions reduce external bias. and Decisions foster trust in plans.

Descriptive vs Prescriptive Analytics

Descriptive: a preliminary stage of data processing that creates a summary of historical data, tells you what happened in the past. Prescriptive: recommends actions you can take to affect those outcomes. Prescriptive analytics is a type of data analytics—the use of technology to help businesses make better decisions through the analysis of raw data. Specifically, prescriptive analytics factors information about possible situations or scenarios, available resources, past performance, and current performance, and suggests a course of action or strategy. It can be used to make decisions on any time horizon, from immediate to long term.

Systematic study

Empirical data gathered through systematic research. Systematic study is a pursuit of knowledge that is methodical; carried on by using step-by-step procedures. Purposefully regular, methodical. Study is the pursuit of knowledge, as by reading, observation, or research, etc.

Which phrase is a description of quality assurance? a. Reactive and causal b. Can be replaced by quality control activities c. Recommends corrective action d. Focuses on training

Focuses on training

Nominal data

Groups of data, no specific order. Nominal data is named data which can be separated into discrete categories which do not overlap. A common example of nominal data is gender; male and female. Other examples include eye colour and hair colour. An easy way to remember this type of data is that nominal sounds like named, nominal = named.

Autocorrelation

In a longitudinal design, the correlation of one variable with itself, measured at two different times. Autocorrelation, also known as serial correlation, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations as a function of the time lag between them.

Mutlicollinearity

In statistics, multicollinearity is a phenomenon in which one predictor variable in a multiple regression model can be linearly predicted from the others with a substantial degree of accuracy.

Interval data

Interval data, also called an integer, is defined as a data type which is measured along a scale, in which each point is placed at equal distance from one another. Interval data always appears in the form of numbers or numerical values where the distance between the two points is standardized and equal. Interval data cannot be multiplied or divided, however, it can be added or subtracted. Interval data is measured on an interval scale. A simple example of interval data: The difference between 100 degrees Fahrenheit and 90 degrees Fahrenheit is the same as 60 degrees Fahrenheit and 70 degrees Fahrenheit. The lack of absolute point zero makes comparisons of direct magnitudes impossible. For example, Object A is twice as large as Object B is not a possibility in interval data.

Which two statements describe how the dedication of leadership and a focus on process enhance quality? choose 2 answers [] it ensures clearly aligned goals [] it enhances customer loyalty [] it makes results easier to manage & achieve [] it ensure a systems appraoch

It ensures clearly aligned goals. ***it makes results easier to manage & achieve***

What does it mean if a researcher said she rejected the null hypothesis at the . 05 level?

It means that there was less than a 5% chance that she would have gotten such an extreme result by chance if the null hypothesis were true. Significance levels The convention in most biological research is to use asignificance levelof0.05. This means that if the Pvalueis less than0.05, you reject the null hypothesis; if P is greater than or equal to0.05, youdon'treject the null hypothesis.

A joint venture is established between two firms to use their core competencies to increase their market share. How would a SIPOC (suppliers, inputs, process, outputs, and customers) diagram benefit the joint venture? a. It tracks financial performance. b. It logs production errors. c. It provides a holistic view of the entire operation. d. It measures client satisfaction.

It provides a holistic view of the entire operation.

What are two aspects of data quality management? a. It calculates spurious data. b. It reduces the amount of incomplete data. c. It monitors data input rates. d. It cleans data.

It reduces the amount of incomplete data. It cleans data.

logistic regression

Logistic regression is the appropriate regression analysis to conduct when the dependent variable is dichotomous (binary). Like all regression analyses, the logistic regression is a predictive analysis. Logistic regression is used to describe data and to explain the relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio-level independent variables. Ex: How does the probability of getting lung cancer (yes vs. no) change for every additional pound a person is overweight and for every pack of cigarettes smoked per day?

Which two attributes indicate potential data quality issues when evaluating a set of nominal data? Choose 2. a. Outlier data b. Missing data c. Out-of-range data d. Misspelled data

Missing data Misspelled data

multivariate regression

Multivariate Regression is a method used to measure the degree at which more than one independent variable (predictors) and more than one dependent variable (responses), are linearly related. ... A mathematical model, based on multivariate regression analysis will address this and other more complicated questions.

A company is trying to increase its online sales revenue by improving its e-mail advertising campaign for repeat customers as well as new customers. Which two variables would be used in determining a campaign to maximize revenue gain? Choose 2. a. Number of purchases per e-mail b. E-mail content c. Spending per purchase d. Cost per e-mail

Number of purchases per e-mail Spending per purchase

Which type of data are the Olympic medals of gold, silver, and bronze examples of? a. Nominal data b. Ordinal data c. Interval data d. Ratio data

Ordinal data

Ordinary Least Squares Regression

Ordinary least squares, or linear least squares, estimates the parameters in a regression model by minimizing the sum of the squared residuals. This method draws a line through the data points that minimizes the sum of the squared differences between the observed values and the corresponding fitted values.

A check sheet indicates that of 100 returned items, 50 were damaged upon delivery, 30 were the wrong size, 10 were of poor quality, 5 were a mistaken order, and 5 were returned due to the customer no longer wanting the item. What is the appropriate way to represent these data? a. construct a control chart b. construct a cause-and-effect diagram c. construct a Pareto chart d. construct a flow chart

Pareto Chart

An organization is concerned about whether quality control standards are being met and develops a strategy to test quality control metrics. Which step does this represent in the Plan-Do-Check-Act cycle? a. Plan b. Do c. Check d. Act

Plan

Probability theory

Probability theory is the mathematical framework that allows us to analyze chance events in a logically sound manner. The probability of an event is a number indicating how likely that event will occur. This number is always between 0 and 1, where 0 indicates impossibility and 1 indicates certainty.

Ratio Data

Ratio Data is defined as a quantitative data, having the same properties as interval data, with an equal and definitive ratio between each data and absolute "zero" being a treated as a point of origin. In other words, there can be no negative numerical value in ratio data. or example: Four people are randomly selected and asked how much money they have with them. Here are the results : $20, $40, $60, and $80. Is there an order to this data? Yes, $20 < $40 < $60 < $80. Are the differences between the data values meaningful? Sure, the person who has $40 has $20 more than the person with $20. Can we calculate ratios based on this data? Yes because $0 is the absolute minimum amount of money a person could have with them. The person with $80 has 4 times as much as the person with $20. Ratio data has all properties of interval data such as - data should have numeric values, a distance between the two points are equal etc. but, unlike interval data where zero is arbitrary, in ratio data, zero is absolute.

Which of Ishikawa's Seven Basic Tools of Quality is used to illustrate performance measurements over time? a. Flowchart b. Pareto chart c. Cause and effect diagram d. Run chart

Run chart

A doctoral student is surveying chief executive officers (CEOs) to understand their relationships with their governing boards. The student determines the years of business experience for each CEO as well as their rating, on a 10-point scale, of satisfaction with the governing board.Which statistical approach should be used to display the data for analysis? a. Scatter plot b. Bell curve c. Mean d. Median

Scatter plot

A soft-drink manufacturer performs a control chart analysis and the results indicate that the soft-drink bottles are consistently under-filled by a large amount according to specifications. The system was evaluated three months prior and was determined to be stable and filling bottles within accepted limits. What is this consistent under-filling an example of? a. Incapable process b. Common cause variation c. Subjective cause variation d. Special cause variation

Special cause variation

When conducting a study that measures an individual's weight, all scales are calibrated prior to use in measurement. Which type of error should this procedure significantly reduce? a. Systematic error b. Omission error c. Random error d. Information error

Systematic error

Several missing values in a particular field in a dataset were observed. The likelihood of a record having a missing value is correlated to another variable in the dataset. Which two types of error might be introduced into the dataset if the removed record included missing values? Choose 2. a. Systematic error b. Omission error c. Random error d. Typographical error

Systematic error Omission error

Dependent Variable (DV)

The measured outcome of a study; the responses of the subjects in a study.

p-value

The probability level which forms basis for deciding if results are statistically significant (not due to chance).

Incapable Process

The process potential index, or Cp, measures a process's potential capability, which is defined as the allowable spread over the actual spread. The allowable spread is the difference between the upper specification limit and the lower specification limit. The standard deviation quantifies a process's variability. As the standard deviation increases in a process, the Cp decreases in value. As the standard deviation decreases (i.e., as the process becomes less variable), the Cp increases in value. By convention, when a process has a Cp value less than 1.0, it is considered potentially incapable of meeting specification requirements. Conversely, when a process Cp is greater than or equal to 1.0, the process has the potential of being capable. Ideally, the Cp should be as high as possible. The higher the Cp, the lower the variability with respect to the specification limits. In a process qualified as a Six Sigma process (i.e., one that allows plus or minus six standard deviations within the specifications limits), the Cp is greater than or equal to 2.0.

An advertising manager creates a research study by presenting low, medium, or high frequency of the same ad in matched markets. The manager then reports on sales in each market location. What is the term for the different sales in this study? a. The experimental unit b. The treatment c. The response variable d. The intervention

The response variable

p-value < 0.05

The smaller the p-value, the stronger the evidence that you should reject the null hypothesis. A p-value less than 0.05 (typically ≤ 0.05) is statistically significant. It indicates strong evidence against the null hypothesis, as there is less than a 5% probability the null is correct (and the results are random).

Mode

The value that occurs most frequently in a given data set.

Biased manageral decisions

They explained that psychological bias - also known as cognitive bias - is the tendency to make decisions or take action in an illogical way. Three types of bias can be distinguished: information bias, selection bias, and confounding.

Homoscedasticity

This assumption means that the variance around the regression line is the same for all values of the predictor variable (X). The plot shows a violation of this assumption. For the lower values on the X-axis, the points are all very near the regression line.

match each action with the appropriate statistical procedure. answer options may be used more than once or not at all. compare outcomes of different drug testing results monitor production process understand effective marketing to spend advertising dollars efficiently

Understand effective marketing to spend advertising dollars efficiently = Correlation Monitor production process= Control Charts Compare outcomes of different drug testing results= ANOVA

Special Cause Variation

Unexpected variation in performance that results from a non-random event; unexpected glitches that affect a process, aka "Assignable Cause. Unlike common cause variability, special cause variation is caused by known factors that result in a non-random distribution of output. Also referred to as "exceptional" or "assignable" variation. Example: Few X's with big impact. Special cause variation is a shift in output caused by a specific factor such as environmental conditions or process input parameters. It can be accounted for directly and potentially removed and is a measure of process control. ex: Let's say you are driving to work, and you estimate arrival in 10 minutes every day. One day, it took you 20 minutes to arrive at work because you were caught in the traffic from an accident zone and were held up. Examples relating to project management are if machine malfunctions, a computer crashes, there is a power cut, etc. These kinds of random things that can happen during a project are examples of special cause variation. One way to evaluate a project's health is to track the difference between the original project plan and what is happening. Use of control charts helps to differentiate between the Common Causes and the Special Causes of Variation, making the process of making changes and amends easier.

Common Cause Variation

Variation that occurs as a natural part of a process; The source of variation in a process that is inherent within the process. Common Cause of Variance = referred to as "Natural Problems, "Noise," and "Random Cause". Common cause variation is fluctuation caused by unknown factors resulting in a steady but random distribution of output around the average of the data. It is a measure of the process potential, or how well the process can perform when special cause variation removed. ex: Consider an employee who takes a little longer than usual to complete a specific task. He is given two days to do a task, and instead, he takes two and a half days; this is considered a common cause of variation. Here's another example: you estimate 20 minutes to get ready and ten minutes to get to work. Instead, you take five minutes extra getting ready because you had to pack lunch and 15 additional minutes to get to work because of traffic. Other examples that relate to projects are inappropriate procedures, which can include the lack of clearly defined standard procedures, poor working conditions, measurement errors, normal wear and tear, computer response times, etc. These are all common cause variations.

weighted least squares regression

Weighted Least Squares is an extension of Ordinary Least Squares regression. Non-negative constants (weights) are attached to data points. It is used when any of the following are true: Your data violates the assumption of homoscedasticity. You want to concentrate on certain areas

Pareto chart

a bar graph whose bars are drawn in decreasing order of frequency or relative frequency. A Pareto Diagram or Chart is a bar chart that re-orders the categories so they are rank-ordered from the largest total occurrences to the smallest. In process analysis, this helps identify the most frequently occurring problems or defect - so it is useful "to separate the vital few from the useful many." The correct ranking for the Pareto chart categories from left to right would be from highest to lowest. A Pareto chart useful When analyzing the frequency of root cause data and you want to focus on the most significant contributors (the vital few).

Pareto Chart

a line/curve graph with a Vertical bar graph on which bar height reflects frequency or impact of causes. A Pareto Chart is a graph that indicates the frequency of defects, as well as their cumulative impact. Pareto Charts are useful to find the defects to prioritize in order to observe the greatest overall improvement. In order to expand on this definition, let's break a Pareto Chart into its components

z-score

a measure of how many standard deviations you are away from the norm (average or mean)

z-score

a measure of how many standard deviations you are away from the norm (average or mean). The value of the z-score tells you how many standard deviations you are away from the mean. ... A positive z-score indicates the raw score is higher than the mean average. For example, if a z-score is equal to +1, it is 1 standard deviation above the mean. A negative z-score reveals the raw score is below the mean average.

R squared

a measure of the strength of a linear relationship. After fitting a linear regression model, you need to determine how well the model fits the data. Does it do a good job of explaining changes in the dependent variable? R-squared is a goodness-of-fit measure for linear regression models. This statistic indicates the percentage of the variance in the dependent variable that the independent variables explain collectively.

F statistic

a ratio of two measures of variance: (1) between-groups variance, which indicates differences among sample means, and (2) within-groups variance, which is essentially an average of the sample variances or A statistical test to determine the relationship between the variances of two or more samples.

Run Charts vs. Control Charts

a run chart is a line graph with data plotted over time; control charts include control limits.

ordinal data

a type of data that refers solely to a ranking of some kind. ordinal data is placed into some kind of order by their position. An example of ordinal data is rating happiness on a scale of 1-10. In scale data there is no standardised value for the difference from one score to the next.

ANOVA (analysis of variance)

an inferential statistical test for comparing the means of three or more groups -differences among MEANS of continuous (numerical) variables -more flexible than t-tests-->can analyze differences among MORE THAN 2 groups (even if diff sample sizes)

Chi-square analysis

assesses how closely the observed frequencies fit the pattern of the expected frequencies and is referred to as a "goodness-of-fit" test. The Chi Square statistic is commonly used for testing relationships between categorical variables. The null hypothesis of the Chi-Square test is that no relationship exists on the categorical variables in the population; they are independent.

a researcher looks at moving average data on store sales & wishes to perform a multiple regression of interest rates & disposable income. what is a particular concern when performing time series multiple regression? a. autocorrelation b. mutlicollinearity c. homosedasticity d. heteroscedasticity

autocorrelation

a hardware store has found that there is a .25 probability that a customer buys an electrical product, a .45 probability that a customer buys a plumbing product and a .10 probability that a customer buys an electrical part if they purchase a plumbing part. given this info., which statistical rule can be used to determine the probability that a customer buys a plumbing product given that this customer has purchased an electrical product? a. multiplication b. conditional probability c. combination d. bayes' theorem

bayes' theorem

A researcher concludes that bananas create healthy children becasue the researcher's notes indicate that children who eat a banana every day are healthy. Which misuse of statistics would this study be an example of if these children also eat a balanced diet & exercise daily? a. faulty operationalization b. unfounded assumptions c. lack of blinding d. confusion of association & causality

confusion of association & causality

In the month of Dec, there is a strong positive correlation between airline ticket sales & retail sales. which question should the researcher consider before concluding that the correlation statistic implies that airline sales drive retail sales? a. is the sample size large enough b. are the data biased c. does a casual relationship truly exist d. does the sample accurately reflect the population

does a casual relationship truly exist

A hotel chain is interested in improving its customer service by reducing the amount of time it takes customers to check in. Which analysis technique should they use? a. tree diagram b. matrix diagram c. flowchart d. network diagram

flowchart

Control Charts

graphical ways of displaying trends so that exceptions to quality standards can be identified. The control chart is a graph used to study how a process changes over time. Data are plotted in time order. A control chart always has a central line for the average, an upper line for the upper control limit, and a lower line for the lower control limit. These lines are determined from historical data.

What are 2 reasons for the increasing use of analytics in organizations? Choose 2 answers. higher computer processing power higher cost of obtaining data lower availability of satistical experts relatively lower cost of computer storage

higher computer processing power relatively lower cost of computer storage

if significance level is 0.05 --> then what is confidence interval?

if your significance level is 0.05, the corresponding confidence level is 95%. If the P value is less than your significance (alpha) level, the hypothesis test is statistically significant. If the confidence interval does not contain the null hypothesis value, the results are statistically significant.

which approach focuses on eliminating activities that do not add value or satisfy customers? a. six sigma b. lean operations c. international organization of Standardization (ISO) cert. d. design for six sigma

lean operations

a company that raises turkeys is hoping to increase the rate of growth of the birds while controlling the cost of feeding the birds. it has determined that feeds containing both nutrients and protein can be used. which decision-making technique is most appropriate for this company to minimize the cost of feeding the birds? a. z-score b. Chi-square c. correlation d. linear programming

linear programming

Attribute Data

measures qualitative dimensions or conditions

a manager is analyzing a dataset that includes information on individual incomes. the mgr knows that the dataset is fairly representative of the general population & includes several millionaires. based on this dataset, which measure of central tendency best represents the middle of the distribution? a. frequency b. median c. mode d. mean

median = middle of the distribution

a medical care provider determines the probability that a patient needs treatment for a broken bone, the probability that a patient needs treatment for a concussion, and the probability that a patient needs treatment for both a broken bone & concussion. which two rules should be used to find the probability that a patient needs treatment for a broken bone and a concussion? Choose 2. multiplication principle union intersection mutually exclusive

multiplication principle intersection

a researcher wants to predict test scores based upon hours spent studying. which type of regression would be more appropriate? a. weighted least squares regression b. multivariate regression c. ordinary least squares regression d. logistic regression

ordinary least squares regression

A college is reviewing statistics concerning student retention. The college would like to determine the most important factors that cause students to leave and asks the researcher to display this information using one of the Seven Basic Tools of Quality. Which tool should be used in this case? histogram run chart flow cart pareto chart

pareto chart

How does probability theory inform decision-making for managers? by: quantifying quality quantifying risk quatifying costs qyantifying datat

quantifying risk

a company decides to auction excess inventory on an auction website. they have performed a regression analyst to identify the length of the auction impacts the final price. which statistic indicates the strength of the relationship between the length of auctions and final price? a. z-score b. f-statistic c. r-squared d. p-value

r-squared

an analyst used multiple linear regression to explore how Store A's sales (y) are predicted by Store A's advertising expenditure dollars (variablex1) and the advertising expenditures dollars of Store A's competitor (variablex2). The estimated regression is y = 532 +80.5x1 - 35.6x2. which scenario would be predicted if x1 is $1000 and x2 is also $1000? a. sales of $45432 b. sales of $116632 c. sales of $44367 d. sales of $44900

sales of $45,432

which graphical tool is used to illustrate a possible relationship or correlation between 2 variables? a. scatterplot b. histogram c. run chart d. box plot

scatterplot or scatter diagram

a retail store notices a spike in turkey sales every November. Which time series patter are turkey sales likely to exhibit? a. seasonality b. cyclicality c. white noise d. trend

seasonality or seasonal

after evaluating manufacturing times for a particular product, a mgr determines that the times are spread out across the distribution. the mgr has been asked to determine how far on average the time is from the mean. which statistical roughly measures the average distance of a data point from the mean of the distribution? a. arithmetic mean b. median c. mode d. standard deviation

standard deviation

p-value < 0.05

statistically significant AND therefore reject the null hypothesis

cohort study

study that measures variables of a group of people over time A cohort study is a particular form of longitudinal study that samples a cohort (a group of people who share a defining characteristic, typically those who experienced a common event in a selected period, such as birth or graduation), performing a cross-section at intervals through time.

a research study examined the impact of product advertisement exposure on that product's brand awareness. the appropriate statistical test indicates that the null hypothesis should be rejected with 95% confidence. what can be concluded from this study? a. 5% of the subjects did not like the advertisement b. the advertisement was effective in building brand awareness c. 95% of the subjects like the brand d. the advertisement was effective in increasing sales

the advertisement was effective in building brand awareness

mean

the arithmetic average of a distribution, obtained by adding the scores and then dividing by the number of scores average

what does it mean when an individual data paint has a z-score of -2? a. the data point is greater than the mean of the data set b. the data point is equal to the mean of the data set c. the data point is is 2 SD less than the mean of the data set d. the sample SD of the data set is negative

the data point is is 2 SD less than the mean of the data set

a manager uses a linear regression to examine how the store's retail sales are predicted by advertising expenditures. what will retail sales represent in this regression? a. the dependent variable b. the independent variable c. the predictor variable d. the control variable

the dependent variable

Median

the middle score in a distribution; half the scores are above it and half are below it

Independent Variable (IV)

the variable that a researcher actively manipulates, and if the hypothesis is correct, will cause a change in the dependent variable

a doctoral student is surveying CEOs to understand their relationships with their governing boards. the student receives responses to a survey w/ 10 questions that rates the respective relationships. why would the student measure the SD of response? a. to measure the spread of the data b. to determine if the data is nonlinear c. to understand the midpoint location of the data d. to create a bell curve

to measure the spread of the data