Q.6.
Both t test and z test are used to determine if two population means are equal or unequal. If we have known variance, we use a two-sample z test. If variance is unknown, we use a two-sample t test.
D Question 6 5 pts What model would you use in a hypothesis test the difference...
3. The table below shows the regression output of a multiple regression model relating the beginning salaries of employees in a given company to the following independent variables: Sex : an indicator variable (1=man and 0-woman) ducation years of schooling at the time of hire Experience number of months of previous work experience Source Regression Residual Total Df 4 8822,387,82 254,407 92 MS F-value 23.763,297 5,940,82423.35 46,151,118 Coefficient table Variable Constant Sex Education Experience Months t-value 10.94 6.02 3.22 2.16...
please calculate the regressional model, the test hypothesis, the rejection region for the test statistic t, the test statistic t, and the percentage of total variation Help A regional retailer would like to determine if the variation in average monthly store sales can, in part, be explained by the size of the store measured in square foot. A random sample of 21 stores was selected and the store size and average monthly sales were computed Complete parts a through c....
Question 2 1 pts In an ANOVA test comparing several population means, if the alternative hypothesis is true, the F statistic tends to be close to zero. True False Question 3 1 pts If the two variables in a two-way table are not associated, the conditional distributions in the table are similar to each other. O True False Question 4 1 pts In a multiple regression model, if the P-value associated with the F test is less than the significance...
QUESTION 6 For this question, you should load the R library wooldridge, first. This can be done by : library(wooldridge). Then import "cps91" to answer the question. Question : You would like to estimate the marginal effects of age, education, experience on hourly wage. The variables are labeled as age, educ, exper, and hwage respectively. What would be the regression equation you would estimate? Olwage = Bo +Bleduc +Bzexper+Bzage + u; Ohrwage = Be + Bleduc +Bzexper+B3age + u; Ohrwage...
Question 3 (5 points) Question 1(C): You have performed a simple linear regression model to understand the effect of Number of Bedrooms on House Price House Price is in Thousand S and Number of Bedrooms is in number of bedrooms Coefficient t-statistic p-value Intercept 28.77 6.52 <0.000 Number of Bedrooms 13.27 9.18 <0.000 Which of the below statement is true. Select one option from below: O p-value<0.001 implies that we cannot reject the null hypothesis. O p-value<0.001 implies that the...
Question 9 5 pts Major League Baseball Games The following scatter plot shows the number of home runs versus the number of attendance (in 1000 people) for some randomly selected games. Attendance and Runs for 11 Baseball Games. 6 8 10 Runs 2 4 O 20 30 40 -50 Attandance x1000) The following shows the output generated by a software for the least-square regression line using this data: Simple linear regression results: Runs - 1.020 +0.1590 Attendance Sample size: 11...
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high (above 0.8), while none of the estimated coefficients are (individually) statistically different from zero at the 5-percent level of significance. The most likely reason for this result is: O multicollinearity. omitted variable bias. O serial correlation. spurious regression. 3 pts Question 9
Heat Power is a utility company that would like to predict the monthly heating bill for a household in a particular region during the month of January. A random sample of 18 households in the region were selected and their January heating bill recorded. The data is shown in the table below along with the square footage of the house (SF), the age of the heating system in years (Age), and the type of heating system (Type: heat pump =...
Question 8 3 pts Suppose you estimate a multiple regression model using OLS and the coefficient of determination is very high (above 0.8), while none of the estimated coefficients are (individually) statistically different from zero at the 5-percent level of significance. The most likely reason for this result is: omitted variable bias. o serial correlation. spurious regression. o multicollinearity.
Question 13 2.5 pts For Questions 13 - 22, consider the following scenario: An analyst for an e-commerce website would like to use a regression model to predict the total amount that customers spend per order. The analyst theorizes that income may help explain order total. An a = 0.05 significance level will be used for this analysis. The analyst randomly samples customers. Total Order Amount was measured in dollars, Income in thousands, The data was used to estimate a...