A marketing professor at Givens College is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 10 students who took thecourse last quarter follow.HoursTotalSpent StudyingPoints Earned45403035907560651059065509090808055457565(a) Develop an estimated regression equation showing how total points earned can be predicted from hours spent studying. (Round your numerical values to two decimal places.) (b) Test the significance of the model with a = 0.05. (Use the Ftest.)State the null and alternative hypotheses.O Ho: P1= 0H B, +oO Hg: B1 0B, z o1.O Ho: Po+0H Po= 0७ H,: B, + 0H B1-0O Ho: Bo = 0H Bo# 0%3DFind the value of the test statistic. (Round your answer to two decimal places.)Find the p-value. (Round your answer to three decimal places.)p-value =ww.State your conclusion.O Do not reject H,. We conclude that the relationship between hours spent studying and total points earned is significant.Reject H. We cannot conclude that the relationship between hours spent studying and total points earned is significant.O Do not reject H,. We cannot conclude that the relationship between hours spent studying and total points earned is significant.O Reject H, We conclude that the relationship between hours spent studying and total points earned is significant.:(c) Predict the total points earned by Mark Sweeney. He spent 85 hours studying. (Round your answer to two decimal places.)points(d) Develop a 95% prediction interval for the total points earned by Mark Sweeney. (Round your answers to two decimal places.)points topoints

Using Excel megastat > regression :using above output: y^ = 5.85 + 0.83 xthe null and alternative hypothesis are: H0 : β1 = 0 H0 : β1 ≠ 0 test statistic = 57.42 P-value = 0.000 since, p-value < 0.05, reject H0 conclusion: Reject H0, we conclude that relationship between hours spent studying and total points earned is significant.Predicted Point = 76.36prediction interval: 57.75 points to 94.97 points

Math

Statistics

A marketing professor at Givens College is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 10 students who took the course last quarter follow. Hours Total Spent Studying Points Earned 45 40 30 35 90 75 60 65 105 90 65 50 90 90 80 80 55 45 75 65 (a) Develop an estimated regression equation showing how total points earned can be predicted from hours spent studying. (Round your numerical values to two decimal places.)

A marketing professor at Givens College is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 10 students who took the course last quarter follow. Hours Total Spent Studying Points Earned 45 40 30 35 90 75 60 65 105 90 65 50 90 90 80 80 55 45 75 65 (a) Develop an estimated regression equation showing how total points earned can be predicted from hours spent studying. (Round your numerical values to two decimal places.)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Related questions

Q: Bill wants to explore factors affecting work stress. He would like to examine the relationship…

Q: Weight (lbs.) 173 184 194 214 168 220 188 188 207 167 217 Systolic Blood Pressure 132 143 153 162…

A: Weight(lbs.)173184194214168220188188207167217Systolic Blood…

Q: (a) Fit the simple linear regression model to this data. (Round your numerical values to three…

A: (a) let first we find the simple regression equation using R >…

Q: A study about workplace bullying used multiple regression to model a bullying victim's intention to…

A: Multiple linear regression model: A multiple linear regression model is given as y = b0 + b1x1 +…

Q: The following table shows the hot dogs bought from a street vendor over the course of eight days…

A: Linear regression measures the linear relationship between one dependent variable(or response…

Q: The table below shows the average weekly wages (in dollars) for state government employees and…

Q: A study about workplace bullying used multiple regression to model a bullying victim's intention to…

A: Multiple linear regression model: A multiple linear regression model is given as y = b0 + b1x1 +…

Q: A Realtor examines the factors that influence the price of a house in Arlington, Massachusetts. He…

A: Regression: The regression tool is used to predict the dependent variable at a given value of the…

Q: A specialist in hospitality states that the number of Room Sold per month in a hotel (RS) can be…

A: From the Given information, Y: The number of rooms(RS) X: Online advertising amounts(QA) x y…

Q: Team sales personnel think that merchandise sales at their upcoming sporting event could be related…

A: We can use the excel data analysis tool to find the answer to the given question. The steps are as…

Q: The table below shows the number of millions of internet users in a particular region. Let x…

Q: The value of a sports franchise is directly related to the amount of revenue that a franchise can…

A: It is given that The dependent variable is franchise value (Y) and the independent variable is…

Q: The table below shows the average weekly wages (in dollars) for state government employees and…

A: We are given the equation of the regression line as,

Q: A magazine publishes restaurant ratings for various locations around the world. The magazine rates…

A: Given data: x y 55 38 68 51 67 59 65 57 63 44 60 38 52 42 65 43 53 33 48 31…

Q: The scatterplot below shows the relationship between left forearm (LeftArm) and right forearm…

A: Solution: The scatterplot shows the the strong positive linear relationship between Left forearm and…

Q: Listed below are paired data consisting of movie budget amounts and the amounts that the movies…

A: Let X : Budget ($) in Millions and Y: Gross ($) in Millions Find the regression equation, letting…

Q: High Concept Fashion is planning its next advertising campaign to coincide with its store expansion…

A: As per the guidelines, the answer to one question is provided only. Post the other question under…

Q: 23 An accountant monitors the number of items produced per month by a company, together with the…

A: Solution-: Let, X=Number of items (000') and Y=Production costs (000') We have following table:…

Q: The following table shows worldwide sales of a type of phone and their average selling prices in…

A: Consider the regression line q=mp+b. Where q is the demand or sales of the smartphones in billions,…

Q: The owners of a chain of ice cream stores have the business objective of improving the forecast of…

A: Solution

Q: Develop an estimated regression equation with annual income and household size as the independent…

A: The regression equation for one independent variable is, Where, y denotes the dependent variable.…

Q: The value of a sports franchise is directly related to the amount of revenue that a franchise can…

A: A scatter plot is a graphical representation of two variables to investigate if there exists an…

Q: The following table shows the reported net sales by Nokia in 2008, 2009, and 2010. Year 2008…

A: The following table shows the reported net sales by Nokia, Year 2008 2009 2010 x 0 1 2 Sales…

Q: Is It Getting Harder to Win a Hot Dog Eating Contest? Every Fourth of July, Nathan’s Famous in New…

A: Hi! Thank you for the question, As per the honour code, we are allowed to answer three sub-parts at…

Q: Construct and interpret a 99% prediction interval for the average weekly wages of federal government…

A: Given data : X Y 713 1002 760 1045 785 1091 805 1145 851 1185 870 1239 921…

Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

A marketing professor at Givens College is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 10 students who took the
course last quarter follow.
Hours
Total
Spent Studying
Points Earned
45
40
30
35
90
75
60
65
105
90
65
50
90
90
80
80
55
45
75
65
(a) Develop an estimated regression equation showing how total points earned can be predicted from hours spent studying. (Round your numerical values to two decimal places.)

(b) Test the significance of the model with a = 0.05. (Use the Ftest.)
State the null and alternative hypotheses.
O Ho: P1= 0
H B, +o
O Hg: B1 0
B, z o
1.
O Ho: Po+0
H Po= 0
७ H,: B, + 0
H B1-0
O Ho: Bo = 0
H Bo# 0
%3D
Find the value of the test statistic. (Round your answer to two decimal places.)
Find the p-value. (Round your answer to three decimal places.)
p-value =
ww.
State your conclusion.
O Do not reject H,. We conclude that the relationship between hours spent studying and total points earned is significant.
Reject H. We cannot conclude that the relationship between hours spent studying and total points earned is significant.
O Do not reject H,. We cannot conclude that the relationship between hours spent studying and total points earned is significant.
O Reject H, We conclude that the relationship between hours spent studying and total points earned is significant.
:(c) Predict the total points earned by Mark Sweeney. He spent 85 hours studying. (Round your answer to two decimal places.)
points
(d) Develop a 95% prediction interval for the total points earned by Mark Sweeney. (Round your answers to two decimal places.)
points to
points

Expert Solution

This question has been solved!

Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.

This is a popular solution!

SEE SOLUTION Check out a sample Q&A here

Statistical software output:

Sol(a)

Sol (b)

Sol(c)

Sol(d)

Trending now

This is a popular solution!

Step by step

Solved in 5 steps with 1 images

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

$Correlation, Regression, and Association$

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.

Similar questions

A cafe company wants to determine how the money they spend on Google ads impacts their monthly revenue. Over 6 consecutive months, they vary the amount they spend on their Ads (in $) and record the associated revenue (in $) for each month. The data is shown below: l Revenue 50 427 75 472 100 467 125 529 150 518 175 543 A) Develop a regression equation for predicting monthly revenue based on the amount spent with Ads. What is the y-intercept? B) What is the sample correlation between these two variables? C) What is the slope of your regression equation? Give your answer to two decimal places. D) Using a 0.05 level of significance, does this regression equation appear to have any value for predicting revenue based on Ads?
Suppose that you are interested in the relationship between Reading and Writing scores. (c) Compute and interpret the R2 value for the relationship between Reading and Writing scores. (d) Interpret the value of the slope in the regression model predicting Reading scores from Writing scores. RDG WRTG 34 44 47 36 42 59 39 41 36 49 50 46 63 65 44 52 47 41 44 50 50 62 44 41 47 40 42 59 42 41 47 41 60 65 39 49 57 54 73 65 47 46 39 44 35 39 39 41 48 49 31 41 52 63 47 54 36 44 47 44 34 46 52 57 42 40 37 44 44 33 71 58 47 46 42 33 42 36 47 41 52 54 52 54 39 39 31 41 60 54 47 31 39 28 42 36 47 57 42 49 36 41 50 33 34 34 55 55 28 46 42 42 44 44 60 52 39 57 36 37 44 44 39 42 39 34 42 39 42 44 52 54 65 65 42 26 47 62 52 62 44 54 52 54 47 44 65 57 63 65 60 59 47 44 65 57 53 61 68 63 55 56 39 53 52 52 65 67 52 44 57 67 63…
The invasive diatom species Didymosphenia geminata has the potential to inflict substantial ecological and economic damage in rivers. An article described an investigation of colonization behavior. One aspect of particular interest was whether y = colony density was related to x = rock surface area. The article contained a scatterplot and summary of a regression analysis. Here is representative data. x 50 71 55 50 33 58 79 26 y 157 1934 53 27 7 10 40 12 x 69 44 37 70 20 45 49 y 274 43 176 18 48 190 30 (a) Fit the simple linear regression model to this data. (Round your numerical values to three decimal places.) y = Predict colony density when surface area = 70 and calculate the corresponding residual. (Round your answers to the nearest whole number.) colony density corresponding residual Predict colony density when surface area = 71 and calculate the corresponding residual. (Round your answers to the nearest whole number.) colony…
The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The following data represents the value in 2014 (in $millions) and the annual revenue (in $millions) for the 30 Major League Baseball franchises. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. Team Revenue Value Baltimore 245 1000 Boston 370 2100 Chicago White Sox 227 975 Cleveland 207 825 Detroit 254 1125 Houston 175 800 Kansas City 231 700 Los Angeles Angels 304 1300 Minnesota 223 895 New York Yankees 508 3200 Oakland 202 725 Seattle 250 1100 Tampa Bay 188 625 Texas 266 1220 Toronto 226 870 Arizona 211 840 Atlanta 267 1150 Chicago Cubs 302 1800 Cincinnati 227 885 Colorado…
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $140 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 39 22 118 67 77 49 124 66 12 64 128 19 6. 147 9. 118 6. 99 75 127 107 95 99 64 109 209 44 8 293 48 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y =+x. (Round to one decimal place as needed.)
Are the years of education of a child dependent on the years of education of their parent? The table shows the number of years of education of parent and the number of years of education of their child. Years of Education of Parent 13 9 7 12 12 10 11 Years of Education of their Child 13 11 7 16 17 9 17 If there is a significant linear correlation between the variables, determine the regression equation. Are the years of education of a child dependent on the years of education of their parent? The table shows the number of years of education of parent and the number of years of education of their child. Years of Education of Parent 13 9 7 12 12 10 11 Years of Education of their Child 13 11 7 16 17 9 17 If there is a significant linear correlation between the variables, determine the regression equation. y’ = 1.5x - 3 There is no significant correlation between the variables,…
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $135 million. Use a significance level of alpha equals 0.05 . Budget left parenthesis $ right parenthesis in Millions 45 24 115 74 72 48 117 67 4 60 124 24 6 152 8 Gross left parenthesis $ right parenthesis in Millions 115 10 95 69 127 112 93 101 50 102 223 26 18 282 56 The regression equation is ŷ = __ + __x. (Round to one decimal place as needed.)
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $105 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 23 114 75 78 47 120 64 10 59 127 22 12 150 2 0 127 18 111 65 113 112 102 94 64 98 211 41 22 288 57 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... x. (Round to one decimal place as needed.) The regression equation is = + The best predicted gross for a movie with a $105 million budget is $ million. (Round to one decimal place as needed.)
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 90% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $825. The equation of the regression line is y = 1.597x- 169.203. Wages (state), x Wages (federal), y 742 775 783 802 842 890 912 939 949 954 1,002 1,039 1,097 1,145 1,199 1,242 1,271 1,299 1,335 1,398 Construct and interpret a 90% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $825. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. There is a 90% chance that the predicted average weekly wages of federal government employees is between S and S given a state average weekly wage of $825. O B. We can be 90%…
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. The equation of the regression line is y = 1.454x- 36.984. Wages (state), x Wages (federal), y 712 778 789 801 843 878 927 937 939 958 1,014 1,054 1,116 1,146 1,191 1,248 1,270 1,302 1,335 1,401 Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. We can be 95% confident that when the average weekly wages of state government employees is $895, the average weekly wages of federal government employees will be between $ and…
Five students took an aptitude test prior to their algebra course. What linear regression equation best predicts algebra performance, based on aptitude scores? If a student made an 80 on the aptitude test, what grade would we expect her to make in algebra? How well does the regression equation fit the data? Student aptitude test algebra grade 1 95 85 2 85 95 3 80 70 4 70 65 5 60 70