SUMMARY OUTPUT Regression Statistics Multiple R 0.69406672 R Square Adjusted R Square Standard Error Observations 0.481728612 0.476440129 3.936905277 100 ANOVA Regression Residual Total df SS MS F 1 1411.826131 1411.82613 91.09012 Significance F 1.18186E-15 98 99 1518.923869 2930.75 15.4992232 Coefficients Standard Error Intercept Father's Age (Death) 29.28584902 0.627659604 4.539696555 t Stat P-value 6.45105872 4.23E-09 0.065764048 9.54411453 1.18E-15 Lower 95% Upper 95% 20.27696896 38.29472909 0.497152992 0.758166217 Lower 95.0% Upper 95.0% 20.27696896 0.497152992 38.29472909 0.758166217 Customer's Age (Death) Excel was used to run a simple linear regression analysis. Excel output and diagnostic plots follow for your reference in answering the remaining questions. 15 Father's Age (Death) Residual Plot Residuals -10 -15 10 10 5 0 40 50 80 90 100 Father's Age (Death) 100 90 80 Normal Probability Plot 70 50 40 30 20 10 0 0 20 40 60 80 100 120 Sample Percentile

Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x

In multiple regression, you can have nominal and continuous predictors true or false

Describe how correlation and regression are linked yet distinct.

Suppose you wanted to test whether or not the payoff to an additional year of education was the same for men and women in the STEM majors. How would you set up your regression analysis in this case

Explain how to find se

What's a good topic for a regression topic? Make sure you have two quantitative variables (for example # of siblings and heart rate). Ask for another variable like academic year, major, hobbies, favorite genre of movie. - State the independent and dependent variables and what is the population.

please answer the third and fourth part

An economist at Nedbank ran a study of the relationship between FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017, the data collected is shown in the Table 1 below. FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017. Year JALSH (Y) CPI (X) 2006 0.41 4.7 2007 0.19 7.1 2008 -0.23 11.5 2009 0.32 7.1 2010 0.19 4.3 2011 0.03 5.0 2012 0.27 5.6 2013 0.21 5.7 2014 0.11 6.1 2015 0.05 4.6 2016 0.00 6.4 2017 0.21 5.3 The estimated regression...