= Simple linear regression results: Dependent Variable: Sales (000) Independent Variable: Advertising (00) Sales (000) =

[answerhappygod]

Simple Linear Regression Results Dependent Variable Sales 000 Independent Variable Advertising 00 Sales 000 1 (100.36 KiB) Viewed 27 times

Test for significance of β1 at α = 0.05 and at α = 0.01
using the t calculated or
t STAT value from the computer
output, and the appropriate values from the t table.
State clearly the null and alternate
hypotheses. Show the
computer table with the t values. State the table
[tcritical] and calculated
[tSTAT] values of t and your conclusion
and why.
= Simple linear regression results: Dependent Variable: Sales (000) Independent Variable: Advertising (00) Sales (000) = 52.048356 +5.860735 Advertising (00) Sample size: 21 R (correlation coefficient) = 0.75863798 R-sq = 0.57553159 Estimate of error standard deviation: 8.1024063 Parameter estimates: Parameter Estimate Std. Err. Alternative DF T-Stat P-value Intercept 52.048356 6.5658149 0 19 7.9271739 <0.0001 Slope 5.860735 1.1546847 #0 19 5.0756152 <0.0001 Analysis of variance table for regression model: Source DF SS MS F-stat P-value Model 1 1691.2407 1691.2407 25.76187 <0.0001 Error 19 1247.3308 65.648987 Total 20 2938.5714
Fitted line Sales (000) 100 90 8010 70 60 50+ 4 6 8 E Advertising (00)