A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR millions. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below:   Which of the independent variables in the model are significant at the 5% level? Formulate the hypothesis and explain the answer. How far can you rely upon this model? Or, what is the percentage variation in House explained by the model? What is the predicted house size (in hundreds of square feet) for an individual earning an annual income of IDR 400 million and having a family size of 4?

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?

A researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: ??=?+????+????+???I Where FR = yearly foreign reserves ($000’s), OIL = annual oil prices, EXP = yearly total exports ($000’s) and FDI = annual foreign direct investment ($000’s). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 Oil 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 * 0.0057 FDI -396.99 160.66 -2.471 ** S = 2.45               R – sq = 96.3%                 R – sq (adj) = 95.3% Analysis of Variance Source DF SS MS F P Regression 3 1991.31 663.77 ? ?? Error 12 77.4 6.45     Total 15           e) Perform the F Test making sure to state…

To determine the effectiveness of group study sessions, a college instructor gathers data on hours of attendance and exam scores for students in the class. Which variable, hours of attendance or exam scores, would be the response variable for a least-squares regression equation? is it hours of attendance or exam scores?

Describe a hypothetical study for which multiple regression with more than two predictor variables would be an appropriate analysis. Your description should include one dependent variable and three or more predictors.

Plzzz explain

Use the summary statistics to calculate the regression line for this data. Explain each coefficient. What is the total amount of weight would you expect a weightlifter with a body weight of 84kg to lift? At the 5% significance level, is there evidence that the body weight of the athlete is a useful predictor for the total amount an athlete can lift? Assume the assumptions can be verified.

APPLIED STATISTICS  UPVOTE WILL BE GIVEN. PLEASE ANSWER THE PROBLEM BY USING SPSS OR EXCEL ONLY (NOT HANDWRITTEN). NO LONG EXPLANATION NEEDED. TAKE A SCREENSHOTS AND ANSWER THE QUESTION IN SENTENCES.   The electric energy consumed each month by a manufacturingwarehouse is imagined to be linked to the ambient temperature, the number of days monthly, average product concentration, and products produced. The annual data based on last year are presented in the following table: a. Estimate the multiple regression equation. b. What is the r-squared value and what is its implication? c. What variable/s are considered significant? What is the p-value?

Consider a regression model. The coefficient of determination (R2) gives the proportion of the variability in the dependent variable that is explained by the regression equation.   True False

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