The cost of attending your university/college has once again gone up. One of theadministrators at your university/college tells you that you pay more because thereputation of your institution is better than that of others. To investigate this hypothesis,you collect data randomly for 100 national universities and liberal arts colleges from the2000-2001 U.S. News and World Report annual rankings. Next you estimate thefollowing regression equation (p-values are in brackets).Cost = 7,311.17+3,985.20 i Reputation – 0.20 i Size(2,058.63) (664.58)(0.11)+ 8,406.79 i Dpriv – 416.38 i Dlibart – 2,376.51 i Dreligion(2,154.85)(1,121.92)(1,007.86)R²= 0.72The numbers in parentheses (brackets) are standard errors.Where:Cost is Tuition, Fees, Room and Board in dollarsReputation is the index used in U.S. News and World Report (based on a surveyof university presidents and chief academic officers), which ranges from 1("marginal") to 5 (“distinguished")Size is the number of undergraduate studentsDpriv, Dlibart, and Dreligion are separate dummy variables indicating whetherthe institution is private or not private, i.e. public [Dpriv]; a liberal arts college ornot liberal arts [Dlibart]; and has a religious affiliation or is not religious[Dreligion].(a) Interpret the coefficients of the variables below and test to determine whetheror not the coefficients are significantly different from zero at the alpha=5%level. (Show your work). What would be the problem if you could not claimthe coefficients are different from zero?(i)Reputation(ii)Dpriv(b) To save money, you are willing to switch from a private university to a publicuniversity, which has a ranking of 0.5 less and 10,000 more students. What is theeffect on your cost? (c) Does there seem to be a difference in cost between a liberal arts college andone that is not liberal arts? Explain.

Answered: The cost of attending your…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Advertising aimed at teenagers tends to contain dance-beat music, adventure, and a fast pace rather than words. To test to see how teenagers respond to different types of commercials, 150 teenagers then watched a set of commercials with dance-beat music, adventure, and a fast pace. After the commercials, the teenagers were asked whether they would want to buy the product and 102 responded that they would buy the product. Another sample of 125 teenagers where shown a set of commercialscomprised primarily of words. After the commercials, the teenagers were asked whether they would buy the product and 60 responded that they would like to buy the product. Based on both samples, at the 5% level of significance, test the hypothesis that there is at least a 10% difference in the proportion of teenagers who would buy the product after watching the different types of commercials?
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for five randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 0 1 3 4 5 Overall Grades 95 92 85 81 62 Table Step 1 of 6 : Find the estimated slope. Round your answer to three decimal places.
You are interested in whether there are gender differences in voting behaviour using the European Social Survey. Youestimate a regression model with being a woman as the single explanatory variable. Clearly write down the regression model.
The Core grade point is the eventual dependent variable in a regression analysis. Look at the correlations between all variables. Is multicollinearity likely to be a problem? Why or why not?
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 47 48 56 60 67 Bone Density 359 350 334 314 313 Find the estimated slope. Round your answer to three decimal places.
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 37 40 52 60 67 Bone Density 352 351 336 329 319. Find the estimated slope. Round your answer to three decimal places
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 0 0.5 2 3 4.5 5 6 Overall Grades 99 98 96 92 89 88 80 Table Step 6 of 6 : Find the value of the coefficient of determination. Round your answer to three decimal places.
Because colas tend to replace healthier beverages and colas contain caffeine and phosphoric acid, researchers wanted to know whether cola consumption is associated with lower bone mineral density in women. The accompanying data lists the typical number of cans of cola consumed in a week and the femoral neck bone mineral density for a sample of 15 women. Complete parts (a) through (d) below. Click the icon to view the women's data. (a) Find the regression equation treating cola consumption per week as the x-variable. y=x+ (Round to three decimal places as needed.) (b) Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. OA. For 0 colas consumed in a week, the bone density is predicted to be (Round to three decimal places as needed.) g/cm³. OB. For every cola consumed per week, the bone density decreases by (Round to three decimal places as needed.) g/cm³, on average. OC. For a bone density of 0 g/cm³, the number of colas…
Does more education lower a person’s level of prejudice? The number of years of education and the score on a prejudice test for ten people is given in the following table. Higher scores on the test indicate more prejudice. Years of Education: 12, 15, 14, 13, 18, 10, 16, 12, 10, 4Score of Prejudice Test: 1, 6, 2, 3, 2, 4, 1, 5, 5, 10 The regression equation is calculated to be y' = 10.5 - 0.532x. After conducting a hypothesis test, your decision is to reject the null hypothesis. Predict the value of y' when x=11. 10.5 4.645 1.945 0.749
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Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 30 minutes. How does the result compare to the actual tip amount of $4.70? Use a significance level of 0.05. Distance 1.80 12.71 1.32 Time 1.65 8.51 1.40 1.02 2.47 Fare Tip 25.00 27.00 8.00 16.30 36.80 7.80 9.80 31.75 12.30 1.50 0.00 0.00 1.96 2.98 2.46 11.00 31.00 18.00 8.00 18.00 7.80 14.30 2.34 4.29 The regression equation is ŷ =+ (x. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.)
You do a survey where you ask people both their age and their income. You want to see if there is a relationship between these two variables, and you want to create an equation you can use to predict someone’s age from his/her income. What kind of hypothesis test or analysis should you do?a. One-Factor, Independent-Measures ANOVAb. Two-Factor ANOVAc. Correlation/Regressiond. Chi-Square Goodness of Fit

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