Homework #3. SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question.

Similar documents
q3_2 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

Chapter 3 CORRELATION AND REGRESSION

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

STAT 201 Chapter 3. Association and Regression

3.2A Least-Squares Regression

M 140 Test 1 A Name SHOW YOUR WORK FOR FULL CREDIT! Problem Max. Points Your Points Total 60

(a) 50% of the shows have a rating greater than: impossible to tell

Math 075 Activities and Worksheets Book 2:

Chapter 3 Review. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question.

M 140 Test 1 A Name (1 point) SHOW YOUR WORK FOR FULL CREDIT! Problem Max. Points Your Points Total 75

Lecture 6B: more Chapter 5, Section 3 Relationships between Two Quantitative Variables; Regression

Regression Equation. November 29, S10.3_3 Regression. Key Concept. Chapter 10 Correlation and Regression. Definitions

AP Statistics Practice Test Ch. 3 and Previous

(a) 50% of the shows have a rating greater than: impossible to tell

STATISTICS INFORMED DECISIONS USING DATA

Math 124: Module 2, Part II

INTERPRET SCATTERPLOTS

BIVARIATE DATA ANALYSIS

Lecture 12: more Chapter 5, Section 3 Relationships between Two Quantitative Variables; Regression

Relationships. Between Measurements Variables. Chapter 10. Copyright 2005 Brooks/Cole, a division of Thomson Learning, Inc.

HW 3.2: page 193 #35-51 odd, 55, odd, 69, 71-78

Sample Applied Skills Problems Grade 10 Math

CHAPTER 3 Describing Relationships

UF#Stats#Club#STA#2023#Exam#1#Review#Packet# #Fall#2013#

1.4 - Linear Regression and MS Excel

Chapter 3: Examining Relationships

3.4 What are some cautions in analyzing association?

Chapter 3: Describing Relationships

Chapter 4: More about Relationships between Two-Variables Review Sheet

10/4/2007 MATH 171 Name: Dr. Lunsford Test Points Possible

bivariate analysis: The statistical analysis of the relationship between two variables.

Chapter 4: More about Relationships between Two-Variables

Homework 2 Math 11, UCSD, Winter 2018 Due on Tuesday, 23rd January

SCATTER PLOTS AND TREND LINES

Unit 8 Bivariate Data/ Scatterplots

Chapter 1: Exploring Data

CRITERIA FOR USE. A GRAPHICAL EXPLANATION OF BI-VARIATE (2 VARIABLE) REGRESSION ANALYSISSys

Multiple Choice Questions

Lesson 1: Distributions and Their Shapes

Section 3.2 Least-Squares Regression

Unit 3 Lesson 2 Investigation 4

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

q2_2 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

STATISTICS & PROBABILITY

Results & Statistics: Description and Correlation. I. Scales of Measurement A Review

Diurnal Pattern of Reaction Time: Statistical analysis

3. For a $5 lunch with a 55 cent ($0.55) tip, what is the value of the residual?

3.2 Least- Squares Regression

Lab 4 (M13) Objective: This lab will give you more practice exploring the shape of data, and in particular in breaking the data into two groups.

STAT 135 Introduction to Statistics via Modeling: Midterm II Thursday November 16th, Name:

Unit 8 Day 1 Correlation Coefficients.notebook January 02, 2018

How Faithful is the Old Faithful? The Practice of Statistics, 5 th Edition 1

REVIEW FOR MATH 0306 FINAL EXAM. 2) Write the expanded notation for )

Name MATH0021Final Exam REVIEW UPDATED 8/18. MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

REVIEW PROBLEMS FOR FIRST EXAM

Unit 1 Exploring and Understanding Data

ANALYZING BIVARIATE DATA

7) Briefly explain why a large value of r 2 is desirable in a regression setting.

Reminders/Comments. Thanks for the quick feedback I ll try to put HW up on Saturday and I ll you

STT 200 Test 1 Green Give your answer in the scantron provided. Each question is worth 2 points.

Multiple Regression. James H. Steiger. Department of Psychology and Human Development Vanderbilt University

1 Version SP.A Investigate patterns of association in bivariate data

STATISTICS 201. Survey: Provide this Info. How familiar are you with these? Survey, continued IMPORTANT NOTE. Regression and ANOVA 9/29/2013

c. Construct a boxplot for the data. Write a one sentence interpretation of your graph.

Chapter Three in-class Exercises. MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

Midterm STAT-UB.0003 Regression and Forecasting Models. I will not lie, cheat or steal to gain an academic advantage, or tolerate those who do.

5 To Invest or not to Invest? That is the Question.

14.1: Inference about the Model

DO NOT OPEN THIS BOOKLET UNTIL YOU ARE TOLD TO DO SO

Examining Relationships Least-squares regression. Sections 2.3

Homework Linear Regression Problems should be worked out in your notebook

Math MidTerm Exam & Math Final Examination STUDY GUIDE Spring 2011

CCM6+7+ Unit 12 Data Collection and Analysis

2.75: 84% 2.5: 80% 2.25: 78% 2: 74% 1.75: 70% 1.5: 66% 1.25: 64% 1.0: 60% 0.5: 50% 0.25: 25% 0: 0%

How to interpret scientific & statistical graphs

Semester 1 Final Scientific calculators are allowed, NO GRAPHING CALCULATORS. You must show all your work to receive full credit.

Further Mathematics 2018 CORE: Data analysis Chapter 3 Investigating associations between two variables

UNIVERSITY OF TORONTO SCARBOROUGH Department of Computer and Mathematical Sciences Midterm Test February 2016

Understandable Statistics

Stat 13, Lab 11-12, Correlation and Regression Analysis

Scatter Plots and Association

STOR 155 Section 2 Midterm Exam 1 (9/29/09)

10. Introduction to Multivariate Relationships

7) Find the sum of the first 699 positive even integers. 7)

12.1 Inference for Linear Regression. Introduction

Introduction to regression

AP Stats Chap 27 Inferences for Regression

Statistical Reasoning in Public Health 2009 Biostatistics 612, Homework #2

Announcement. Homework #2 due next Friday at 5pm. Midterm is in 2 weeks. It will cover everything through the end of next week (week 5).

MEASURES OF ASSOCIATION AND REGRESSION

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

Class 7 Everything is Related

Dr. Allen Back. Oct. 7, 2016

2) {p p is an irrational number that is also rational} 2) 3) {a a is a natural number greater than 6} 3)

Analysis and Interpretation of Data Part 1

Elementary Algebra Sample Review Questions

Table of Contents. Plots. Essential Statistics for Nursing Research 1/12/2017

Pearson Education Limited Edinburgh Gate Harlow Essex CM20 2JE England and Associated Companies throughout the world

Standard Deviation and Standard Error Tutorial. This is significantly important. Get your AP Equations and Formulas sheet

Chapter 14. Inference for Regression Inference about the Model 14.1 Testing the Relationship Signi!cance Test Practice

Transcription:

Homework #3 Name Due Due on on February Tuesday, Due on February 17th, Sept Friday 28th 17th, Friday SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. Fill in the blank. 1) A association between two quantitative variables x and y is present if y tends to go down as x goes up. 1) 2) The is a summary measure that describes the strength of the linear association between two quantitative variables. 2) MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 3) Suppose you were to collect data for the pair of given variables in order to make a scatterplot. For the variables cloudy days and rainy days, which is more naturally the response variable and which is the explanatory variable? A) Cloudy days: explanatory variable Rainy days: response variable B) Cloudy days: response variable Rainy days: explanatory variable 3) In 2006, the General Social Survey asked Do you strongly agree, agree, disagree or strongly disagree that it is sometimes necessary to discipline a child with a good, hard spanking? The responses are cross-tabulated with the respondent s gender in the table below. Favor Spanking? Gender Strongly Agree Agree Disagree Strongly Disagree Total Male 238 419 165 41 863 Female 294 474 237 102 1107 Total 532 893 402 143 1970 4) Which variable is the explanatory variable? 4) A) Gender B) Response to whether the respondent favors spanking 5) What proportion of males responded that they agree with spanking as a means of disciplining a child? A) 0.28 B) 0.21 C) 0.49 D) 0.12 E) 0.76 5) Select the most appropriate answer. 6) The is the outcome variable on which comparisons are made. 6) A) predictor variable B) Both B and C C) response variable D) explanatory variable E) lurking variable 1

In 2006, the General Social Survey asked Do you strongly agree, agree, disagree or strongly disagree that it is sometimes necessary to discipline a child with a good, hard spanking? The responses are cross-tabulated with the respondent s gender in the table below. Favor Spanking? Gender Strongly Agree Agree Disagree Strongly Disagree Total Male 238 419 165 41 863 Female 294 474 237 102 1107 Total 532 893 402 143 1970 7) Which gender is more likely to respond that they agree that it is sometimes necessary to discipline a child with spanking? A) Neither, they are both equally likely to offer this response B) Men C) Women 8) Overall, what proportion of people responded that they strongly disagree with spanking as a form of discipline? A) 0.05 B) 0.07 C) 0.09 D) 0.02 7) 8) Answer true or false. 9) The advantage of a side-by-side bar graph is that it allows for easy comparison of the explanatory variable groups with respect to values on the response variable. A) False B) True 9) The following table summarizes the responses of 1255 adults when asked by the 2006 General Social Survey whether they had ever taken the drug Prozac. Male Female Total Yes 36 96 132 No 495 628 1123 Total 531 724 1255 10) Given that the respondent is male, what is the probability that he responded yes? 10) A) 0.11 B) 0.27 C) 0.03 D) 0.07 11) Given that the respondent answered "Yes", what is the probability that the respondent was female? 11) A) 0.08 B) 0.58 C) 0.13 D) 0.73 2

12) The relationship between the number of games won by a minor league baseball team and the average attendance at their home games is analyzed. A regression to predict the average attendance from the number of games won has an r = 0.73. Interpret this statistic. A) Positive, fairly strong linear relationship. 53.29% of the variation in average attendance is explained by the number of games won. B) No association C) Negative, fairly strong linear relationship. 53.29% of the variation in average attendance is explained by the number of games won. D) Positive, weak linear relationship. 7.29% of the variation in average attendance is explained by the number of games won. E) Positive, fairly strong linear relationship. 73% of the variation in average attendance is explained by the number of games won. 12) 13) A random sample of records of electricity usage of homes gives the amount of electricity used in July and size (in square feet) of 135 homes. A regression was performed to predict the amount of electricity used (in kilowatt-hours) based on size. The residuals plot indicated that a linear model is appropriate. Do you think the slope is positive or negative? Why? A) Positive. Larger homes should use more electricity. B) Positive. More square feet indicates more houses. C) Negative. Smaller homes should use less electricity. D) Positive. The larger the number of houses the more electricity used. E) Negative. Larger homes should use less electricity. 14) Would you expect the following pair of variables measured for 200 individuals aged 18-32 to have a positive association, negative association, or no association: amount of time spent exercising per week; height? A) no association B) negative association C) positiveassociation 13) 14) Determine the type of association apparent in the following scatterplot. 15) 15) A) Negative association, moderately strong association B) Little or no association C) Positive association, moderately strong association D) Positive association, linear association E) Negative association, linear association 3

16) 16) A) Linear association, moderately strong association B) Positive association, moderately strong association C) Positive association, moderately strong association, linear association D) Positive association E) Linear association Answer true or false. 17) A scatterplot is a graphical display for two quantitative variables. 17) A) True B) False 18) For the 14 teams in baseball s American league, the correlation with number of wins in the 2007 regular season is 0.51 for shutouts, 0.61 for hits made, -.70 for runs allowed and -0.56 for homeruns allowed. Which variable has the weakest linear association with number of wins? A) homeruns allowed B) runs allowed C) shutouts D) hits made 18) Answer true or false. 19) The closer r is to 0, the weaker is the linear association between the variables. 19) A) True B) False 20) The value of the correlation is always between 0 and 1. 20) A) True B) False 21) Based on findings from the Health and Nutrition Examination Survey conducted by the National Center for Health Statistics from April 1971 to June 1974, the regression equation predicting the average weight of a male aged 18-24 (y) based on his height (x) is given by y = -172.63 + 4.842x. (www.cdc.gov/nchs/data/ad/ad014acc.pdf) What is the best prediction for the weight of a male aged 18-24 who is 70 inches tall? Round your answer to the nearest pound. A) y B) 166 C) 339 D) 70 22) Nine data points of data yield r = 0.867 and the regression equation y = 19.4 + 0.93x. Also, y = 64.7. What is the best predicted value of y for x = 40? A) 37.2 B) 57.8 C) 64.7 D) 56.6 E) 79.6 21) 22) 4

Select the most appropriate answer. 23) The slope is the 23) A) predicted value of y. B) predicted value of y when x = 0. C) change in the predicted value of y per unit increase in x. D) point where the regression line crosses the y-axis. E) smallest value for the residual sum of squares. 24) A regression line for predicting the selling prices of homes in Chicago is y = 168 + 102x, where x is the square footage of the house. A house with 1500 square feet recently sold for $140,000. What is the residual for this observation? A) 13,168 B) 1316.80 C) 13,000 D) -13,168 E) -13,000 25) A regression line for predicting Interenet usage (%) for 39 countries is y = -3.61 + 1.55x, where x is the per capita GDP, in thousands of dollars, and y is Internet usage. Interpret the residual for one of the 39 countries with per capita GDP of $15,000 and actual Internet use of 20 percent. A) The actual Internet usage for this country is 3.6% higher than expected from the regression B) The actual Internet usage for this country is 0.36% lower than expected from the regression C) The actual Internet usage for this country is 3.25% lower than expected from the regression D) The actual Internet usage for this country is 0.36% higher than expected from the regression E) The actual Internet usage for this country is 3.25% higher than expected from the regression 24) 25) Select the most appropriate answer. 26) The prediction error for an observation, which is the difference between the actual value and the predicted value of the response variable, is called. A) an extrapolation B) an intercept C) a correlation D) an outlier E) a residual 26) Fill in the missing information. 27) x sx y sy r y = a + bx 40 20 8 11 8 y =? A) -154 + 4.4x B) -168 + 4.4x C) 175 + 2.2x D) -38 + 4.4x E) -168+2.2x 27) 5

28) x sx y sy r y = a + bx?? 18 4-0.5 y = 30-4x A) x = 3; sx = 0.50 B) x = 12; sx = 2.00 C) x = 12; sx = 1.00 D) x = 3; sx = 1.00 E) x = 48; sx = -18.00 28) 29) Which of the following has the potential for affecting the relationship between the response and explanatory variable, but was not measured by the study? A) None of these B) All of these C) A confounding variable D) Outliers E) A lurking variable 30) A study of consumer behavior finds a positive correlation between sales of ice cream and sales of soda. What might explain the strong correlation? A) No lurking variable B) Ice cream creates a thirst for soda C) People generally have ice cream for dessert if they have drunk soda with a meal. D) Arithmetic mistake E) Outdoor temperature 29) 30) 6