Score GPA Hours Absences Gender78 3.15 3.0 4 Female75 2.71 4.0 1 Female79 3.57 3.5 2 Male85 3.26 6.5 0 Female85 3.75 2.0 0 Female84 3.20 4.5 3 Female85 3.16 5.0 3 Male80 3.35 1.5 0 Female74 2.75 3.5 6 Male81 3.04 6.5 1 Male76 2.53 3.0 0 Female85 2.92 6.0 1 Male A business statistics professor would like to develop a regression model to predict the final exam scores for studentsbased on their current GPAS, the number of hours they studied for the exam, the number of times they were absentduring the semester, and their genders. The data for these variables are given in the accompanying table. Completeparts a through e below.Click the icon to view the data table.a. Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen,which equals 1 for a male and 0 for a female student (this assignment is arbitrary).Complete the regression equation for the model below, where y = Score, x₁ = GPA, x₂ = Hours, x3 = Absences, andX4 = Gen.ŷ=+(x₁+x₂ + (x3 +×4(Round to two decimal places as needed.)

Here the dependent variable (y) is the Score for students.There are four independent variables:x1 =…

a. Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen, which equals 1 for a male and 0 for a female student (this assignment is arbitrary). Complete the regression equation for the model below, where y=Score, x₁ =GPA, X₂ = Hours, x3 = Absences, and X4 = Gen.

a. Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen, which equals 1 for a male and 0 for a female student (this assignment is arbitrary). Complete the regression equation for the model below, where y=Score, x₁ =GPA, X₂ = Hours, x3 = Absences, and X4 = Gen.

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

Similar questions

Provide an explanation for the different relationships (if any), that these factors have with the happiness index.
Call centers typically have high turnover. The director of human resources for a large bank has compiled data on about 70 former employees at one of the bank's call centers. The accompanying table shows this data. In writing an article about call center working conditions, a reporter has claimed that the average tenure is no more than two years. Formulate and test a hypothesis using these data to determine if this claim can be disputed. Use a level of significance of 0.05. E Click the icon to view the call center data. .... Is there sufficient evidence at the 0.05 level of significance that the average tenure is no more than two years? Determine the null hypothesis, H,n, and the alternative hypothesis, H,. Call center data Ho: H,: (Type whole numbers.) Length of service (years) Gender Compute the test statistic. 7.03 O (Round to two decimal places as needed.) 1 3.48 2.07 Find the p-value for the test. 1.78 4.41 O (Round to three decimal places as needed.) 3.28 State the conclusion.…
Forecast the average number of viewers during the 2009 season using a three-period weighted moving average with weights 3, 2, and 1, applying 3 to the most recent data and 1 to the oldest data.
Check O Resources Give Up? O Hint ent Score: 5.9% 2 of 16 Beans and other legumes are a great source of protein. The following data give the protein content of 30 different varieties of beans, in grams per 100 grams of cooked beans. 7.5 8.2 8.9 9.3 7.1 8.3 8.7 9.5 8.2 9.1 Make a proper stemplot of these data. 9.0 9.0 9.7 9.2 8.9 8.1 9.0 7.8 8.0 7.8 6 8 7 0 1556788 8 0 112 2333799 9 0 00 1 2357 10 6 7.0 7.5 13.5 8.3 6.8 10.6 8.3 7.6 7.7 8.1 11 12 13 5 O 18 01556788 8 0 1122333709 900 0 12 357 10 6 7. 11 12 13 6 Key: 618=6.8 grams of protein per 100g of cooked beans 0 1 755678 8 80 1122 333 8799 000123 957 106 11 7. 12 135 Key: 68 68 grams of protein per 100g of cooked beans 68 7 61880667 8. 29372910331 9 35 100720 10 6 11 12 13 5
Stocks may be categorized by sectors. The accompanying data represent the one-year rate of return (in percent) for a sample of consumer cyclical stocks and industrial stocks for a 12-month period. Note: Consumer cyclical stocks include restaurants and retailers. Industrial stocks include manufacturers and shipping companies. Complete parts (a) through (c) below. E Click the icon to view the data. (b) Determine the mean and median rate of return for each sector. Which sector has the higher mean rate of return? Which sector has the higher median rate of return? Xconsumer cyclical = Mconsumer cyclical = (Round to three decimal places as needed.)
Ten samples of two dimensional data set is given in the table. Find the principal components of this data. 1.4 1.6 -1.4 -2.0 -3.0 2.4 1.5 2.3 -3.2 -4.1 1.65 1.97 -1.77 -2.52 -3.95 3.07 2.03 2.80 -4.05 -4.85
(e) The third quarter for the following data is 39, 29 , 20, 17, 38, 39, 14, 30, 32, 36, 14 i. 36 ii. 38 iii. 39 iv. 20 v. none of the above
9th Grade 10th grade 11th grade 12th grade 6 10 17 15 9 12 8 16 6 11 11 12 7 11 14 12 7 14 15 12 Calculate mean square within group
A market analyst wants to know if the new website he designed is showing increased page views per visit. A customer is randomly sent to one of two different websites, offering the same products, but with different designs. The accompanying table shows the data from 30 randomly chosen customers from each website. Assume that the data come from a distribution that is Normally distributed. Complete parts a through c below. Click the icon to view the data table and summary statistics of website page views per visit. a) Find a 95% confidence interval for the mean difference, PA - HB, in page views from the two websites. (Round to two decimal places as needed.) C
Gender Alcohol Exercise SQI GPA Male Yes 9 15.5 3.85 Male Yes 11 11.0 5.46 Female No 5 11.1 3.28 Female No 6 13.9 2.37 Female Yes 8 9.9 4.63 Male Yes 11 14.5 4.58 Male Yes 9 10.6 4.96 Male Yes 11 15.1 1.02 Female No 8 12.4 4.33 Female Yes 10 11.5 3.96 Male No 8 10.6 5.83 Male Yes 7 11.5 6.12 Male Yes 10 10.8 2.20 Male Yes 11 12.5 2.93 Male Yes 9 16.4 4.52 Female Yes 2 14.1 4.50 Male Yes 8 15.3 1.63 Female No 6 18.0 3.09 Female No 5 9.7 3.92 Male Yes 11 10.5 3.10 Female No 8 13.7 5.42 Male Yes 8 14.9 2.03 Female No 7 10.9 5.90 Male No 10 14.5 3.25 Male Yes 7 11.5 5.21 Female No 9 11.3 3.31 Male Yes 9 11.6 2.51 Male No 10 15.6 3.88 Male Yes…
Job sat. Absence Quality Output Week score rate score score 1 3.40 0.05 0.88 8 2 3.60 0.04 0.89 10 3 3.70 0.06 0.90 9 4 3.80 0.03 0.92 10 10 5 3.90 0.04 0.83 8 6 4.20 0.03 0.91 10 7 4.00 0.04 0.92 9 8 4.10 0.05 0.83 9 Weekly goals: Job satisfaction score ≥ 4.50, Absence rate ≤ 0.03, Quality score ≥ 0.95, Output score ≥9 Over the last four weeks, how is the team doing compared to the quality goal?
In an advertising campaign, a snack company claimed that every 18-ounce bag of its cookies contained at least 1000 chocolate chips. Two statisticians attempted to verify the claim. The accompanying data represent the number of chips in an 18-ounce bag of the company's cookies based on their study. Complete parts (a) through (e). Click here to view the chocolate chip data table Click here to view the standard normal distribution table (page 1). Click here to view the standard normal distribution table (page 2). (a) Draw a normal probability plot to determine if the data could have come from a normal distribution. Choose the correct plot below. O A. OB. O D. 2.5- 2.5- 2.5 2.5 0- -2.5+ 1000 1300 1600 -2.5+ 1000 1300 1600 -2.5 + 1000 1300 -2.5+1- 1000 1300 Observed value 1600 1600 Observed value Observed value Observed value Expected z score