The file contains the selling prices (Y) and the appraised values (X) of the 148 homes.
Construct a 95% confidence interval for the average value of y. Use x = 130,000.
Construct a 95% prediction interval for a single value of y. Use x = 130,000.
Compare the results.
Stock market analysts are continually looking for reliable predictors of stock prices. Consider the problem of modeling the price per share of electric utility stocks (Y). Two variables thought to influence this stock price are return on average equity (X_1) and annual dividend rate (X_2).
The stock price, returns on equity, and dividend rates on a randomly selected day for several electric utility stocks are provided in the file Dataset_stock prices.xlsx sheet named Data.
Use Excel to develop the equation of the regression model. Comment on the regression coefficients. Determine the predicted value of y for x1=12.1 and x2=3.18.
Study the ANOVA table and the t ratios and use these to discuss the strengths of the regression model and the predictors. Does this model appear to fit the data well? Use α = 0.05.
Comment on the overall strength of the regression model in light ofs_e, R2, and adjusted R2.
Attachment:- Data-stock price.rar