9) The following results are from a regression where the dependent variable is GRADUATION RATE and the independent variables are % OF CLASSES UNDER 20, % OF CLASSES OF 50 OR MORE, STUDENT/FACULTY RATIO, ACCEPTANCE RATE, 1ST YEAR STUDENTS IN TOP 10% OF HS CLASS. The data were split into 2 samples and the following regression results were obtained from the split data. a) What is heteroscedasticity? (b) Why is heteroscedasticity a problem? c) Based on a comparison of the two sets of output, does it appear that there is heteroscedasticity in the data set? Explain. Be sure to write down your null and alternative hypothesis, calculate the test statistic, and find your critical value (test at the 5% level of significance).

Explain what a correlation is.How does analyzing the relationship between two variables with correlation differ from using regressionanalysis? How does the interpretation differ from a correlation relative to interpreting output from aregression?

What is the Small Values of Squared Correlation Coefficient?

A group of researchers followed 10 firms from 2010 to 2022 to determine the effect of new tax policies on firms' performance: Firm ID = 1,...,10 Year = 2010,...,2022 I2010 = Investment during year in 2010 ... I2022 = Investment during year in 2022 F2010 = Real Value of the Firm in 2010 ... F2010 = Real Value of the Firm in 2022 What type of data set is this?   a. time-series   b. panel (longitudinal)   c. none of the above   d. cross-section

10) The following results are from a regression where the dependent variable is COST OF COLLEGE and the independent variables are TYPE OF SCHOOL which is a dummy variable = 0 for public schools and = 1 for private schools, FIRST QUARTILE SAT which is the average score of students in the top quartile of SAT’s, THIRD QUARTILE SAT which is the average score of students in the 3rd quartile, and ROOM AND BOARD which is the cost of room and board at the school. The first set of results includes all the independent variables whereas the second set of results excludes the THIRD QUARTILE SAT variable. a) Based on these two sets of data, does there appear that multicollinearity is a problem (specifically, does it appear that THIRD QUARTILE SAT is highly collinear with the other independent variables? Explain. b) Calculate the VIF for THIRD QUARTILE SAT. c) Based on the VIF, do you think that multicollinearity is a problem? Explain.

Step 1 (a) What is an estimate of the proportion of calls not resulting in a satisfactory outcome for the customer when the center is in control? A proportion of the calls not resulting in a satisfactory outcome is to be found. This proportion will have the following form. number of unsatisfactory outcome calls proportion total number of calls There were 10 samples, each with 100 calls. Therefore, the total number of calls is 10(100) = The given data represent the number of calls in samples of 100 that resulted in unsatisfactory resolution of customer calls. 6. 4 4 4 7 8 The total number of calls not resulting in a satisfactory outcome will be the sum of the values in the data. The data gives a sum of such calls. Submit Skip (you cannot come back)

What are some of the most basic statistic formulas used in excel for the Hospitality carrier field?

11. Why doesn't correlation equal causation?

Several bakeries in a town were asked the price for different amounts of donuts at their shop. The scatter plot with Total Cost (in dollars) 876543 ~ TO 0 0 1 Donut Pricing 2 3 4 5 Number of Donuts 6 7 8 line of best fit was created from the data gathered. Part A: Estimate the correlation coefficient. Explain your reasoning for the given value. Part B: How many positive and negative residuals are there? Explain your reasoning. Part C: State the point with the largest absolute value residual and interpret the point in terms of the context of the data.

True or false .If there is no linear correlation between enrollment and the number of burglaries , then those two variables are not related in anyway. Explain why ?