# Good luck! BUSINESS STATISTICS FINAL EXAM INSTRUCTIONS. Name:

Size: px
Start display at page: ## Transcription

2 For questions 1-3, indicate the type of data described. 1. (1 pt) In a web-based survey, customers are asked to rate your company s product on the following scale: Excellent, good, average, poor. (a) Continuous (b) Ordinal (c) Nominal (d) None of the above 2. (1 pt) In the same survey, customers are asked to provide their gender: male or female. (a) Continuous (b) Ordinal (c) Nominal (d) None of the above 3. (1 pt) As part of a quality improvement program, your mail order company records the length of time every customer spends on hold waiting to place their order via the telephone. (a) Continuous (b) Ordinal (c) Nominal (d) None of the above 4. (2 pts) Calculate the median of the following set of data: 123, 243, 322, 492, 537, 599, 620, 798, 812, 954. (a) 537 (b) 550 (c) 568 (d) 599 (e) None of the above are correct. 5. (2 pts) If you have a data set that consists of the following three values 1, 2, and 3, which of the following statements are true: (a) The range of the data is 3. (b) The sample standard deviation equals the sample average. (c) The sample standard deviation equals the sample variance. (d) Both (a) and (b) are true. (e) None of the above are true. 6. (1 pt) For CEO salaries throughout the entire United States (not just the data set we used in class), which has a distribution that is skewed to the right with some very large outliers, which is greater: the average salary or the median salary? (a) Average salary (b) Median salary (c) Cannot determine from the information given 1

3 7. (1 pt) The inter-quartile range equals the 75th percentile minus the 25th percentile. For questions 8-10: You are the senior vice-president in charge of production for a company that manufactures two different types of widgets. You manage three divisions. You are interested in displaying various types of data about your company. Select the one technique from each list that is most applicable. 8. (2 pts) In order to summarize production for the past month, both broken down by the number of each type of widget produced by each division, as well as the total number of each type of widget produced and the total production for each division, you would use a: (a) Scatterplot (b) Contingency table (c) Confidence interval (d) Side-by-side boxplot (e) Histogram 9. (2 pts) You also want to graphically assess whether there is a positive association between total daily production level (measured in terms of the dollar value of good widgets produced) and daily cost of scrap and re-work (measured in the cost in dollars of lost materials and labor to correct errors) across the divisions for the past 90 days. The best way to evaluate this is to use a: (a) Scatterplot (b) Contingency table (c) Confidence interval (d) Side-by-side boxplot (e) Histogram 10. (2 pts) You now want to graphically compare the distribution of salaries for midlevel managers between your three manufacturing divisions. Each division has between 37 and 80 mid-level managers. The best way to display the information for this purpose is with a: (a) Scatterplot (b) Contingency table (c) Confidence interval (d) Side-by-side boxplot (e) Histogram 11. (1 pt) A number is drawn at random from a box. There is a 20% chance for it to be less than 10. There is a 10% chance for it to be more than 50. So, the chance of getting a number between 10 and 50 (inclusive) is 70%. 2

4 12. (1 pt) The Central Limit Theorem says that for large sample sizes the sample mean has an approximately normal distribution. 13. (1 pt) From the empirical rule we can deduce that, for any distribution, 95% of the observations fall between the mean plus or minus two standard deviations. 14. (1 pt) As the number of degrees of freedom increase, the t distribution gets closer and closer to the normal distribution. 15. (2 pts) As the district sales manager for a franchise fast-food company, you prefer to compare sales performance in terms of standardized values. Having just hired a new analyst, you demonstrate for her how to standardize the value x = 20 given = 10 and = 5. Show your work. Solution: Z = (x - ) / = (20 10) / 5 = (2 pts) You are now looking at a computer printout of the daily sales for 100 franchise stores in your sales district prepared by the new analyst. The daily sales values have been standardized by subtracting the average daily sales for all 100 stores and dividing by the standard deviation of the daily sales for the 100 stores. The first 10 entries are: Does the printout look reasonable or is something wrong? (a) The numbers look reasonable. (b) Something is wrong. (c) Need more information about the computer program. 17. (3 pts) Assuming the standardized values (call them X) have a standard normal distribution, using either the tables in the back of your textbook or Excel, find the following probabilities (to four decimal places): (a) Pr(X < 0.5) = (b) Pr(X < 1.5) = (c) Pr(X < 2.5) =

5 18. (2 pts) Based on your Business Statistics class in the Global MBA program, you know that a confidence interval is wider if: (a) A larger sample (n) is used. (b) A larger t or z value is used. (c) It is changed from a 95% CI to a 90% CI. (d) Both (b) and (c). (e) All of the above. 19. (2 pts) A confidence interval inappropriately using a z statistic instead of a t statistic will give a interval. (a) wider (b) narrower 20. (3 pts) If a confidence interval has width 1 based on a sample of 50 observations, what is the width if the sample size is increased to 800 (assuming everything else remains constant)? (a) 0.25 (b) 0.5 (c) 2 (d) 4 (e) Not enough information to determine the answer 21. (1 pt) In a hypothesis test, assuming the conventional critical value for evaluating p-values of 0.05, a p-value greater than 0.05 indicates statistical significance. 22. (1 pt) In a hypothesis test, the null hypothesis says that the observed difference is just due to chance. 23. (2 pts) A paired t-test requires: (a) One sample with two observations on each unit in the sample. (b) Two independent samples. (c) Either a one or two samples depending on the hypotheses. (d) Either a one-sided or two-sided test depending on the p-value. (e) Both (c) and (d). For questions 24-26: You are the sales manager for a large condominium development in Sacramento, California. You are interested in determining how much to price your units for and have collected information on 87 equivalent condominiums that have sold in the past two months in Sacramento. 24. (2 pts) To determine a range of plausible sales prices for your condominiums, you would construct a on the data for the 87 equivalents. (a) Two-sample t-test (b) One-sample t-test (c) Contingency table (d) Confidence interval (e) Mosaic plot 4

7 Assume that in answer to the last question, you analyze the data from the random sample of students grades with a two-sample, two-sided t-test (which may or may not be correct), obtaining the following results: 28. (2 pts) What conclusion do you reach from the above output? (a) Reject the null hypothesis and conclude that the mean GPAs are different. (b) Accept the null hypothesis and conclude that the mean GPAs are different. (c) Reject the null hypothesis and conclude that the mean GPAs are the same. (d) Accept the null hypothesis and conclude that the mean GPAs are the same. (e) None of the above are correct conclusions. 29. (2 pts) What is the interpretation of the Difference value in the table? (a) The average GPA of those in the sample without work experience is points higher than those with work experience. (b) The average GPA of those in the sample with work experience is points higher than those without work experience. (c) Can t determine without looking at the original data. For questions 30-33: Most lenders to individuals use some form of credit scoring system to evaluate applicants for loans. One lender uses such a system with a 0 to 100 scale where higher scores are better. The JMP output below is for a random sample of 400 applicants drawn from a new mailing list. 6

8 30. (2 pts) The lender regards a mailing list to be desirable if the mean credit score is 82 or higher. What can you conclude from the output (taken at face value, without regard to any criticism of the study) about the mailing list? (a) We cannot tell much since the sample size is too small. (b) The data are so variable that no conclusion can be reached. (c) The mean score of the mailing list is very likely to be less than 82. (d) The mean score of the mailing list could reasonably be 82, higher or lower. (e) The mean score of the mailing list is very likely to be 82 or higher. 31. (3 pts) Using the above output, which one of the following steps is incorrect (or are all of them are correct) for calculating and interpreting the 95% confidence interval for the population mean credit score of [78.67, 80.02]. (a) The normal quantile plot shows that it is reasonable to assume that the credit scores have a normal distribution. (b) To be most precise, because the population standard deviation is unknown, the t distribution with 399 degrees of freedom should be used in the confidence interval calculation. (c) Given the correct t-value ( t below), you calculate the confidence interval as CI t , t (d) You can interpret the confidence interval to say that 95 percent of the credit scores in the population will fall within the confidence interval. (e) All of the above are true. 32. (2 pts) Your boss, not having taken this class, isn t sure what to make of a confidence interval. She says that what she really wants to know is whether she can be relatively sure the average credit score is 82 or higher. Based on what you know from the confidence interval, what can you tell your boss? (a) Well, 82 is outside of the confidence interval, so you think there s a good chance that the average population score is above 82, but you can t be sure without doing a hypothesis test. (b) Since 82 is above the upper bound of the 95% confidence interval, then a hypothesis test would reject the null hypothesis that the average population score is equal to 82. (c) Since 82 is above the upper bound of the 95% confidence interval, then a hypothesis test would fail to reject the null hypothesis that the average population score is equal to 82. (d) You can t conclude anything about a hypothesis test just from the confidence interval. 33. (2 pts) The manager who selected the sample later said that he had discarded the obvious low and high score and replaced them with scores nearer the average. What is the consequence of this action, as compared with truly random sampling? (a) The mean will definitely be too high. (b) The mean will definitely be too low. (c) The confidence interval will be too wide. (d) The confidence interval will be too narrow. (e) The additional information is irrelevant. 7

9 For questions 34-40: As the regional manager of a pizza franchise business, you are interested in understanding how income in a region affects pizza sales. Below is a regression output for pizza sales (in thousands of dollars) regressed on the average household income of an area (also in thousands of dollars). 34. (2 pts) What is the average pizza sales across all eight regions? (a) \$43.63 (b) \$2, (c) \$14, (d) \$43,625 (e) Cannot determine from the JMP output above. 35. (2 pts) What does the p-value for the income variable ( Income (\$000) ) mean? (a) The slope of the regression line is significantly different from zero. (b) The intercept of the regression line passes through the origin (c) The income of a region is not significant in explaining pizza sales. (d) Both a and c are correct. (e) None of the above. 36. (2 pts) What is the interpretation of the slope? (a) For each \$1,000 increase in average household income, pizza sales increase by \$2.90. (b) For each \$1,000 increase in average household income, pizza sales increase by \$2,905. (c) For each \$2,905 increase in average household income, pizza sales increase by \$1,000. (d) For each dollar increase in average household income, pizza sales increase by \$ (e) None of the above. 8

10 37. (3 pts) What does the model predict for pizza sales in a region with an average household income of \$40,000? (a) \$116 (b) \$131 (c) \$116,205 (d) \$130,768 (e) None of the above. 38. (2 pts) What can you conclude from/about the estimated intercept? (a) For the model s fitted line, when x=0 then the model predicts that y= (b) The model predicts that regions with an average household income of \$0 will still have pizza sales of \$14,577. (c) The intercept must be an extrapolation from the data, since we could not have observed any regions with average household incomes of \$0 (or less). (d) All of the above are appropriate conclusions. (e) None of the above are appropriate conclusions. 39. (2 pts) What is the interpretation of the R 2? (a) 0.968% of the variation in pizza sales is explained by income. (b) 0.968% of the variation in income is explained by pizza sales. (c) 96.8% of the variation in pizza sales is explained by income. (d) 96.8% of the variation in income is explained by pizza sales. (e) None of the above. 40. (2 pts) What is the Root Mean Square Error? (a) It is how far off the intercept is from the origin on average. (b) It is the estimated standard deviation of the error term in the regression model. (c) It is calculated as the square of the mean of the independent variable. (d) Both a and c. (e) None of the above. End of Exam 9

### Part 3. Comparing Groups. Chapter 7 Comparing Paired Groups 189. Chapter 8 Comparing Two Independent Groups 217 Part 3 Comparing Groups Chapter 7 Comparing Paired Groups 189 Chapter 8 Comparing Two Independent Groups 217 Chapter 9 Comparing More Than Two Groups 257 188 Elementary Statistics Using SAS Chapter 7 Comparing

### Name: Date: Use the following to answer questions 3-4: Name: Date: 1. Determine whether each of the following statements is true or false. A) The margin of error for a 95% confidence interval for the mean increases as the sample size increases. B) The margin

### Once saved, if the file was zipped you will need to unzip it. For the files that I will be posting you need to change the preferences. 1 Commands in JMP and Statcrunch Below are a set of commands in JMP and Statcrunch which facilitate a basic statistical analysis. The first part concerns commands in JMP, the second part is for analysis

### Unit 31 A Hypothesis Test about Correlation and Slope in a Simple Linear Regression Unit 31 A Hypothesis Test about Correlation and Slope in a Simple Linear Regression Objectives: To perform a hypothesis test concerning the slope of a least squares line To recognize that testing for a

### Statistics 2014 Scoring Guidelines AP Statistics 2014 Scoring Guidelines College Board, Advanced Placement Program, AP, AP Central, and the acorn logo are registered trademarks of the College Board. AP Central is the official online home

### Lesson 1: Comparison of Population Means Part c: Comparison of Two- Means Lesson : Comparison of Population Means Part c: Comparison of Two- Means Welcome to lesson c. This third lesson of lesson will discuss hypothesis testing for two independent means. Steps in Hypothesis

### THE FIRST SET OF EXAMPLES USE SUMMARY DATA... EXAMPLE 7.2, PAGE 227 DESCRIBES A PROBLEM AND A HYPOTHESIS TEST IS PERFORMED IN EXAMPLE 7. THERE ARE TWO WAYS TO DO HYPOTHESIS TESTING WITH STATCRUNCH: WITH SUMMARY DATA (AS IN EXAMPLE 7.17, PAGE 236, IN ROSNER); WITH THE ORIGINAL DATA (AS IN EXAMPLE 8.5, PAGE 301 IN ROSNER THAT USES DATA FROM

### Statistics 100 Sample Final Questions (Note: These are mostly multiple choice, for extra practice. Your Final Exam will NOT have any multiple choice! Statistics 100 Sample Final Questions (Note: These are mostly multiple choice, for extra practice. Your Final Exam will NOT have any multiple choice!) Part A - Multiple Choice Indicate the best choice

### CHAPTER 14 NONPARAMETRIC TESTS CHAPTER 14 NONPARAMETRIC TESTS Everything that we have done up until now in statistics has relied heavily on one major fact: that our data is normally distributed. We have been able to make inferences

### Simple Regression Theory II 2010 Samuel L. Baker SIMPLE REGRESSION THEORY II 1 Simple Regression Theory II 2010 Samuel L. Baker Assessing how good the regression equation is likely to be Assignment 1A gets into drawing inferences about how close the

### General Method: Difference of Means. 3. Calculate df: either Welch-Satterthwaite formula or simpler df = min(n 1, n 2 ) 1. General Method: Difference of Means 1. Calculate x 1, x 2, SE 1, SE 2. 2. Combined SE = SE1 2 + SE2 2. ASSUMES INDEPENDENT SAMPLES. 3. Calculate df: either Welch-Satterthwaite formula or simpler df = min(n

### NCSS Statistical Software Chapter 06 Introduction This procedure provides several reports for the comparison of two distributions, including confidence intervals for the difference in means, two-sample t-tests, the z-test, the

### An Introduction to Statistics Course (ECOE 1302) Spring Semester 2011 Chapter 10- TWO-SAMPLE TESTS The Islamic University of Gaza Faculty of Commerce Department of Economics and Political Sciences An Introduction to Statistics Course (ECOE 130) Spring Semester 011 Chapter 10- TWO-SAMPLE TESTS Practice

### HYPOTHESIS TESTING: CONFIDENCE INTERVALS, T-TESTS, ANOVAS, AND REGRESSION HYPOTHESIS TESTING: CONFIDENCE INTERVALS, T-TESTS, ANOVAS, AND REGRESSION HOD 2990 10 November 2010 Lecture Background This is a lightning speed summary of introductory statistical methods for senior undergraduate

### Introduction to Quantitative Methods Introduction to Quantitative Methods October 15, 2009 Contents 1 Definition of Key Terms 2 2 Descriptive Statistics 3 2.1 Frequency Tables......................... 4 2.2 Measures of Central Tendencies.................

### Unit 27: Comparing Two Means Unit 27: Comparing Two Means Prerequisites Students should have experience with one-sample t-procedures before they begin this unit. That material is covered in Unit 26, Small Sample Inference for One

### MTH 140 Statistics Videos MTH 140 Statistics Videos Chapter 1 Picturing Distributions with Graphs Individuals and Variables Categorical Variables: Pie Charts and Bar Graphs Categorical Variables: Pie Charts and Bar Graphs Quantitative

### Chapter 7 Section 1 Homework Set A Chapter 7 Section 1 Homework Set A 7.15 Finding the critical value t *. What critical value t * from Table D (use software, go to the web and type t distribution applet) should be used to calculate the

### MINITAB ASSISTANT WHITE PAPER MINITAB ASSISTANT WHITE PAPER This paper explains the research conducted by Minitab statisticians to develop the methods and data checks used in the Assistant in Minitab 17 Statistical Software. One-Way

### MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. STT315 Practice Ch 5-7 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Solve the problem. 1) The length of time a traffic signal stays green (nicknamed

### Confidence Intervals for One Standard Deviation Using Standard Deviation Chapter 640 Confidence Intervals for One Standard Deviation Using Standard Deviation Introduction This routine calculates the sample size necessary to achieve a specified interval width or distance from

### Comparing Means in Two Populations Comparing Means in Two Populations Overview The previous section discussed hypothesis testing when sampling from a single population (either a single mean or two means from the same population). Now we

### Chapter 7 Section 7.1: Inference for the Mean of a Population Chapter 7 Section 7.1: Inference for the Mean of a Population Now let s look at a similar situation Take an SRS of size n Normal Population : N(, ). Both and are unknown parameters. Unlike what we used

### Biostatistics: DESCRIPTIVE STATISTICS: 2, VARIABILITY Biostatistics: DESCRIPTIVE STATISTICS: 2, VARIABILITY 1. Introduction Besides arriving at an appropriate expression of an average or consensus value for observations of a population, it is important to

### Describing, Exploring, and Comparing Data 24 Chapter 2. Describing, Exploring, and Comparing Data Chapter 2. Describing, Exploring, and Comparing Data There are many tools used in Statistics to visualize, summarize, and describe data. This chapter

### Descriptive Statistics Descriptive Statistics Primer Descriptive statistics Central tendency Variation Relative position Relationships Calculating descriptive statistics Descriptive Statistics Purpose to describe or summarize

### LAB 4 INSTRUCTIONS CONFIDENCE INTERVALS AND HYPOTHESIS TESTING LAB 4 INSTRUCTIONS CONFIDENCE INTERVALS AND HYPOTHESIS TESTING In this lab you will explore the concept of a confidence interval and hypothesis testing through a simulation problem in engineering setting.

### BA 275 Review Problems - Week 6 (10/30/06-11/3/06) CD Lessons: 53, 54, 55, 56 Textbook: pp. 394-398, 404-408, 410-420 BA 275 Review Problems - Week 6 (10/30/06-11/3/06) CD Lessons: 53, 54, 55, 56 Textbook: pp. 394-398, 404-408, 410-420 1. Which of the following will increase the value of the power in a statistical test

### Chapter 23 Inferences About Means Chapter 23 Inferences About Means Chapter 23 - Inferences About Means 391 Chapter 23 Solutions to Class Examples 1. See Class Example 1. 2. We want to know if the mean battery lifespan exceeds the 300-minute

### Chapter 7: Simple linear regression Learning Objectives Chapter 7: Simple linear regression Learning Objectives Reading: Section 7.1 of OpenIntro Statistics Video: Correlation vs. causation, YouTube (2:19) Video: Intro to Linear Regression, YouTube (5:18) -

### Statistics courses often teach the two-sample t-test, linear regression, and analysis of variance 2 Making Connections: The Two-Sample t-test, Regression, and ANOVA In theory, there s no difference between theory and practice. In practice, there is. Yogi Berra 1 Statistics courses often teach the two-sample

### Business Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics. Business Course Text Bowerman, Bruce L., Richard T. O'Connell, J. B. Orris, and Dawn C. Porter. Essentials of Business, 2nd edition, McGraw-Hill/Irwin, 2008, ISBN: 978-0-07-331988-9. Required Computing

### Two-Sample T-Tests Assuming Equal Variance (Enter Means) Chapter 4 Two-Sample T-Tests Assuming Equal Variance (Enter Means) Introduction This procedure provides sample size and power calculations for one- or two-sided two-sample t-tests when the variances of

### Lecture Notes Module 1 Lecture Notes Module 1 Study Populations A study population is a clearly defined collection of people, animals, plants, or objects. In psychological research, a study population usually consists of a specific

### Tutorial 5: Hypothesis Testing Tutorial 5: Hypothesis Testing Rob Nicholls nicholls@mrc-lmb.cam.ac.uk MRC LMB Statistics Course 2014 Contents 1 Introduction................................ 1 2 Testing distributional assumptions....................

### Factors affecting online sales Factors affecting online sales Table of contents Summary... 1 Research questions... 1 The dataset... 2 Descriptive statistics: The exploratory stage... 3 Confidence intervals... 4 Hypothesis tests... 4

### Recall this chart that showed how most of our course would be organized: Chapter 4 One-Way ANOVA Recall this chart that showed how most of our course would be organized: Explanatory Variable(s) Response Variable Methods Categorical Categorical Contingency Tables Categorical

### Data Analysis Tools. Tools for Summarizing Data Data Analysis Tools This section of the notes is meant to introduce you to many of the tools that are provided by Excel under the Tools/Data Analysis menu item. If your computer does not have that tool

### SPSS for Exploratory Data Analysis Data used in this guide: studentp.sav (http://people.ysu.edu/~gchang/stat/studentp.sav) Data used in this guide: studentp.sav (http://people.ysu.edu/~gchang/stat/studentp.sav) Organize and Display One Quantitative Variable (Descriptive Statistics, Boxplot & Histogram) 1. Move the mouse pointer

### Chapter 13 Introduction to Linear Regression and Correlation Analysis Chapter 3 Student Lecture Notes 3- Chapter 3 Introduction to Linear Regression and Correlation Analsis Fall 2006 Fundamentals of Business Statistics Chapter Goals To understand the methods for displaing

### Fairfield Public Schools Mathematics Fairfield Public Schools AP Statistics AP Statistics BOE Approved 04/08/2014 1 AP STATISTICS Critical Areas of Focus AP Statistics is a rigorous course that offers advanced students an opportunity

### Statistics I for QBIC. Contents and Objectives. Chapters 1 7. Revised: August 2013 Statistics I for QBIC Text Book: Biostatistics, 10 th edition, by Daniel & Cross Contents and Objectives Chapters 1 7 Revised: August 2013 Chapter 1: Nature of Statistics (sections 1.1-1.6) Objectives

### Stat 411/511 THE RANDOMIZATION TEST. Charlotte Wickham. stat511.cwick.co.nz. Oct 16 2015 Stat 411/511 THE RANDOMIZATION TEST Oct 16 2015 Charlotte Wickham stat511.cwick.co.nz Today Review randomization model Conduct randomization test What about CIs? Using a t-distribution as an approximation

### Chapter 5 Analysis of variance SPSS Analysis of variance Chapter 5 Analysis of variance SPSS Analysis of variance Data file used: gss.sav How to get there: Analyze Compare Means One-way ANOVA To test the null hypothesis that several population means are equal,

### Institute of Actuaries of India Subject CT3 Probability and Mathematical Statistics Institute of Actuaries of India Subject CT3 Probability and Mathematical Statistics For 2015 Examinations Aim The aim of the Probability and Mathematical Statistics subject is to provide a grounding in

### Unit 26: Small Sample Inference for One Mean Unit 26: Small Sample Inference for One Mean Prerequisites Students need the background on confidence intervals and significance tests covered in Units 24 and 25. Additional Topic Coverage Additional coverage

### C. The null hypothesis is not rejected when the alternative hypothesis is true. A. population parameters. Sample Multiple Choice Questions for the material since Midterm 2. Sample questions from Midterms and 2 are also representative of questions that may appear on the final exam.. A randomly selected sample

### Hypothesis testing - Steps Hypothesis testing - Steps Steps to do a two-tailed test of the hypothesis that β 1 0: 1. Set up the hypotheses: H 0 : β 1 = 0 H a : β 1 0. 2. Compute the test statistic: t = b 1 0 Std. error of b 1 =

### NCSS Statistical Software Chapter 06 Introduction This procedure provides several reports for the comparison of two distributions, including confidence intervals for the difference in means, two-sample t-tests, the z-test, the

### Exploratory data analysis (Chapter 2) Fall 2011 Exploratory data analysis (Chapter 2) Fall 2011 Data Examples Example 1: Survey Data 1 Data collected from a Stat 371 class in Fall 2005 2 They answered questions about their: gender, major, year in school,

### Course Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics Course Text Business Statistics Lind, Douglas A., Marchal, William A. and Samuel A. Wathen. Basic Statistics for Business and Economics, 7th edition, McGraw-Hill/Irwin, 2010, ISBN: 9780077384470 [This

### STAT 350 Practice Final Exam Solution (Spring 2015) PART 1: Multiple Choice Questions: 1) A study was conducted to compare five different training programs for improving endurance. Forty subjects were randomly divided into five groups of eight subjects

### SCHOOL OF HEALTH AND HUMAN SCIENCES DON T FORGET TO RECODE YOUR MISSING VALUES SCHOOL OF HEALTH AND HUMAN SCIENCES Using SPSS Topics addressed today: 1. Differences between groups 2. Graphing Use the s4data.sav file for the first part of this session. DON T FORGET TO RECODE YOUR

### Premaster Statistics Tutorial 4 Full solutions Premaster Statistics Tutorial 4 Full solutions Regression analysis Q1 (based on Doane & Seward, 4/E, 12.7) a. Interpret the slope of the fitted regression = 125,000 + 150. b. What is the prediction for

### The right edge of the box is the third quartile, Q 3, which is the median of the data values above the median. Maximum Median CONDENSED LESSON 2.1 Box Plots In this lesson you will create and interpret box plots for sets of data use the interquartile range (IQR) to identify potential outliers and graph them on a modified box

### SAUDI SCHOOL ASSESSMENT SYSTEM FOR PREDICTING ADMISSIONS TO SCIENCE COLLEGES SAUDI SCHOOL ASSESSMENT SYSTEM FOR PREDICTING ADMISSIONS TO SCIENCE COLLEGES 1 Khalid Alnowibet, 2 Shafiq Ahmad 1 Department of Statistics and Operations Research, College of Science, King Saud University,

### Week 4: Standard Error and Confidence Intervals Health Sciences M.Sc. Programme Applied Biostatistics Week 4: Standard Error and Confidence Intervals Sampling Most research data come from subjects we think of as samples drawn from a larger population.

### Simple linear regression Simple linear regression Introduction Simple linear regression is a statistical method for obtaining a formula to predict values of one variable from another where there is a causal relationship between

### Summary of Formulas and Concepts. Descriptive Statistics (Ch. 1-4) Summary of Formulas and Concepts Descriptive Statistics (Ch. 1-4) Definitions Population: The complete set of numerical information on a particular quantity in which an investigator is interested. We assume

### Inference for two Population Means Inference for two Population Means Bret Hanlon and Bret Larget Department of Statistics University of Wisconsin Madison October 27 November 1, 2011 Two Population Means 1 / 65 Case Study Case Study Example

### Unit 26 Estimation with Confidence Intervals Unit 26 Estimation with Confidence Intervals Objectives: To see how confidence intervals are used to estimate a population proportion, a population mean, a difference in population proportions, or a difference

### " Y. Notation and Equations for Regression Lecture 11/4. Notation: Notation: Notation and Equations for Regression Lecture 11/4 m: The number of predictor variables in a regression Xi: One of multiple predictor variables. The subscript i represents any number from 1 through

### 1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number 1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number A. 3(x - x) B. x 3 x C. 3x - x D. x - 3x 2) Write the following as an algebraic expression

### t Tests in Excel The Excel Statistical Master By Mark Harmon Copyright 2011 Mark Harmon t-tests in Excel By Mark Harmon Copyright 2011 Mark Harmon No part of this publication may be reproduced or distributed without the express permission of the author. mark@excelmasterseries.com www.excelmasterseries.com

### DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. DESCRIPTIVE STATISTICS The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. DESCRIPTIVE VS. INFERENTIAL STATISTICS Descriptive To organize,

### Analysis of Variance ANOVA Analysis of Variance ANOVA Overview We ve used the t -test to compare the means from two independent groups. Now we ve come to the final topic of the course: how to compare means from more than two populations.

### 1. What is the critical value for this 95% confidence interval? CV = z.025 = invnorm(0.025) = 1.96 1 Final Review 2 Review 2.1 CI 1-propZint Scenario 1 A TV manufacturer claims in its warranty brochure that in the past not more than 10 percent of its TV sets needed any repair during the first two years

### Two-Sample T-Tests Allowing Unequal Variance (Enter Difference) Chapter 45 Two-Sample T-Tests Allowing Unequal Variance (Enter Difference) Introduction This procedure provides sample size and power calculations for one- or two-sided two-sample t-tests when no assumption

### Introduction to Analysis of Variance (ANOVA) Limitations of the t-test Introduction to Analysis of Variance (ANOVA) The Structural Model, The Summary Table, and the One- Way ANOVA Limitations of the t-test Although the t-test is commonly used, it has limitations Can only

### BA 275 Review Problems - Week 5 (10/23/06-10/27/06) CD Lessons: 48, 49, 50, 51, 52 Textbook: pp. 380-394 BA 275 Review Problems - Week 5 (10/23/06-10/27/06) CD Lessons: 48, 49, 50, 51, 52 Textbook: pp. 380-394 1. Does vigorous exercise affect concentration? In general, the time needed for people to complete

### Two-sample t-tests. - Independent samples - Pooled standard devation - The equal variance assumption Two-sample t-tests. - Independent samples - Pooled standard devation - The equal variance assumption Last time, we used the mean of one sample to test against the hypothesis that the true mean was a particular

### 4. Continuous Random Variables, the Pareto and Normal Distributions 4. Continuous Random Variables, the Pareto and Normal Distributions A continuous random variable X can take any value in a given range (e.g. height, weight, age). The distribution of a continuous random

### Using SPSS, Chapter 2: Descriptive Statistics 1 Using SPSS, Chapter 2: Descriptive Statistics Chapters 2.1 & 2.2 Descriptive Statistics 2 Mean, Standard Deviation, Variance, Range, Minimum, Maximum 2 Mean, Median, Mode, Standard Deviation, Variance,

### Introduction. Hypothesis Testing. Hypothesis Testing. Significance Testing Introduction Hypothesis Testing Mark Lunt Arthritis Research UK Centre for Ecellence in Epidemiology University of Manchester 13/10/2015 We saw last week that we can never know the population parameters

### MONT 107N Understanding Randomness Solutions For Final Examination May 11, 2010 MONT 07N Understanding Randomness Solutions For Final Examination May, 00 Short Answer (a) (0) How are the EV and SE for the sum of n draws with replacement from a box computed? Solution: The EV is n times

### Outline. Definitions Descriptive vs. Inferential Statistics The t-test - One-sample t-test The t-test Outline Definitions Descriptive vs. Inferential Statistics The t-test - One-sample t-test - Dependent (related) groups t-test - Independent (unrelated) groups t-test Comparing means Correlation

### MATH 103/GRACEY PRACTICE EXAM/CHAPTERS 2-3. MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. MATH 3/GRACEY PRACTICE EXAM/CHAPTERS 2-3 Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Provide an appropriate response. 1) The frequency distribution

### 1. The parameters to be estimated in the simple linear regression model Y=α+βx+ε ε~n(0,σ) are: a) α, β, σ b) α, β, ε c) a, b, s d) ε, 0, σ STA 3024 Practice Problems Exam 2 NOTE: These are just Practice Problems. This is NOT meant to look just like the test, and it is NOT the only thing that you should study. Make sure you know all the material

### The Dummy s Guide to Data Analysis Using SPSS The Dummy s Guide to Data Analysis Using SPSS Mathematics 57 Scripps College Amy Gamble April, 2001 Amy Gamble 4/30/01 All Rights Rerserved TABLE OF CONTENTS PAGE Helpful Hints for All Tests...1 Tests

### CALCULATIONS & STATISTICS CALCULATIONS & STATISTICS CALCULATION OF SCORES Conversion of 1-5 scale to 0-100 scores When you look at your report, you will notice that the scores are reported on a 0-100 scale, even though respondents

### HYPOTHESIS TESTING WITH SPSS: HYPOTHESIS TESTING WITH SPSS: A NON-STATISTICIAN S GUIDE & TUTORIAL by Dr. Jim Mirabella SPSS 14.0 screenshots reprinted with permission from SPSS Inc. Published June 2006 Copyright Dr. Jim Mirabella CHAPTER

### 3. There are three senior citizens in a room, ages 68, 70, and 72. If a seventy-year-old person enters the room, the TMTA Statistics Exam 2011 1. Last month, the mean and standard deviation of the paychecks of 10 employees of a small company were \$1250 and \$150, respectively. This month, each one of the 10 employees

### II. DISTRIBUTIONS distribution normal distribution. standard scores Appendix D Basic Measurement And Statistics The following information was developed by Steven Rothke, PhD, Department of Psychology, Rehabilitation Institute of Chicago (RIC) and expanded by Mary F. Schmidt,

### Independent t- Test (Comparing Two Means) Independent t- Test (Comparing Two Means) The objectives of this lesson are to learn: the definition/purpose of independent t-test when to use the independent t-test the use of SPSS to complete an independent

### QUANTITATIVE METHODS BIOLOGY FINAL HONOUR SCHOOL NON-PARAMETRIC TESTS QUANTITATIVE METHODS BIOLOGY FINAL HONOUR SCHOOL NON-PARAMETRIC TESTS This booklet contains lecture notes for the nonparametric work in the QM course. This booklet may be online at http://users.ox.ac.uk/~grafen/qmnotes/index.html.

### Study Guide for the Final Exam Study Guide for the Final Exam When studying, remember that the computational portion of the exam will only involve new material (covered after the second midterm), that material from Exam 1 will make

### AP * Statistics Review. Descriptive Statistics AP * Statistics Review Descriptive Statistics Teacher Packet Advanced Placement and AP are registered trademark of the College Entrance Examination Board. The College Board was not involved in the production

### How Does My TI-84 Do That How Does My TI-84 Do That A guide to using the TI-84 for statistics Austin Peay State University Clarksville, Tennessee How Does My TI-84 Do That A guide to using the TI-84 for statistics Table of Contents

### Psychology 60 Fall 2013 Practice Exam Actual Exam: Next Monday. Good luck! Psychology 60 Fall 2013 Practice Exam Actual Exam: Next Monday. Good luck! Name: 1. The basic idea behind hypothesis testing: A. is important only if you want to compare two populations. B. depends on

### Independent samples t-test. Dr. Tom Pierce Radford University Independent samples t-test Dr. Tom Pierce Radford University The logic behind drawing causal conclusions from experiments The sampling distribution of the difference between means The standard error of

### Statistics 151 Practice Midterm 1 Mike Kowalski Statistics 151 Practice Midterm 1 Mike Kowalski Statistics 151 Practice Midterm 1 Multiple Choice (50 minutes) Instructions: 1. This is a closed book exam. 2. You may use the STAT 151 formula sheets and

### Module 3: Correlation and Covariance Using Statistical Data to Make Decisions Module 3: Correlation and Covariance Tom Ilvento Dr. Mugdim Pašiƒ University of Delaware Sarajevo Graduate School of Business O ften our interest in data analysis

### An SPSS companion book. Basic Practice of Statistics An SPSS companion book to Basic Practice of Statistics SPSS is owned by IBM. 6 th Edition. Basic Practice of Statistics 6 th Edition by David S. Moore, William I. Notz, Michael A. Flinger. Published by

### Mind on Statistics. Chapter 12 Mind on Statistics Chapter 12 Sections 12.1 Questions 1 to 6: For each statement, determine if the statement is a typical null hypothesis (H 0 ) or alternative hypothesis (H a ). 1. There is no difference Principles of Statistics STA-201-TE This TECEP is an introduction to descriptive and inferential statistics. Topics include: measures of central tendency, variability, correlation, regression, hypothesis Lecture 1: Review and Exploratory Data Analysis (EDA) Sandy Eckel seckel@jhsph.edu Department of Biostatistics, The Johns Hopkins University, Baltimore USA 21 April 2008 1 / 40 Course Information I Course