9) A good regression model has:
A) ANOVA F Significance greater than 0.05
B) Multicollinearity
C) The fewest number of explanatory variables providing an adequate interpretation of the dependent variable
D) Residuals exhibiting non-random patterns
Ans:
Correct option is C:
The fewest number of explanatory variables providing an adequate interpretation of the dependent variable.
Others are incorrect as:
If p-value>0.05,then model is not signfiicant.
Residuals should exhibit random pattern.
Multicolliniearity leads to error in stimation of coefficients.
9) A good regression model has: A) ANOVA F Significance greater than 0.05 B) Multicollinearity C)...
Based on the ANOVA table given, is there enough evidence at the 0.05 level of significance to conclude that the linear relationship between the independent variables and the dependent variable is statistically significant? ANOVA Source df SS MS F Significance F Regression 33 334.126370334.126370 111.375457111.375457 0.7082900.708290 0.5813510.581351 Residual 66 943.473630943.473630 157.245605157.245605 Total 99 1277.6000001277.600000 Yes or No?
Based on the ANOVA table given, is there enough evidence at the 0.05 level of significance to conclude that the linear relationship between the independent variables and the dependent variable is statistically significant? ANOVA Source df Regression 2 1520.519603 760.259801 8.137791 0.005843 Residual12 1121.080397 93.423366 MS F Significance F Total 14 2641.600000 Copy Data Ne ev Keypad Tables MacBook Ai 44 F FS F6
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...
*ANSWERS IN BOX ARE INCORRECT*
Consider the following ANOVA table for a multiple regression model. Complete parts a through e below. Source Regression 3 3,600 1200 20 Residual 35 2,100 60 Total df SSMSF 38 5,700 a. What is the size of this sample? n41 b. How many independent variables are in this model? c. Calculate the multiple coefficient of determination. R0.5882 Round to four decimal places as needed.) d. Test the significance of the overall regression model using α=0.05...
for b.
the p-value is
(less than 0.01, between 0.01 and 0.025, between 0.025 and 0.05,
between 0.05 and 0.10, or greater than 0.10), we (Reject, Accept)
H0
for c.
the p-value is
(less than 0.01, between 0.01 and 0.025, between 0.025 and 0.05,
between 0.05 and 0.10, or greater than 0.10), we (Reject, Accept)
H0
Check My Work (3 remaining) eBook A regression model relating 2, number of salespersons at a branch office, to y, annual sales at the...
Need help with stats true or false questions
Decide (with short explanations) whether the following statements are true or false a) We consider the model y-Ao +A(z) +E. Let (-0.01, 1.5) be a 95% confidence interval for A In this case, a t-test with significance level 1% rejects the null hypothesis Ho : A-0 against a two sided alternative. b) Complicated models with a lot of parameters are better for prediction then simple models with just a few parameters c)...
A multiple regression model has _____. a. at least two dependent variables b. more than one dependent variable c. more than one independent variable d. only one independent variable
Consider the following results of a multiple regression model of dollar price of unleaded gas (dependent variable) and a set of independent variables: price of crude oil, value of S&P500, price U.S. Dollars against Euros, personal disposal income (in million of dollars) : Coefficient t-statistics Intercept 0.5871 68.90 Crude Oil 0.0651 32.89 S&P 500 -0.0020 18.09 Price of $ -0.0415 14.20 PDI 0.0001 17.32 R-Square = 97% What will be forecasted price of unleaded gas if the value of independent...
The ANOVA summary table to the right is for a multiple regression model with five independent variables. Complete parts (a) through (e). Source Degrees of Freedom Sum of Squares Regression 5 270 Error 28 110 Total 33 380 a. Determine the regression mean square (MSR) and the mean square error (MSE). b. Compute the overall FSTAT test statistic. FSTAT=_______________________ (Round to four decimal places as needed.) c. Determine whether there is a significant relationship between Y and the two independent...
Regression Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Warranty_Yearsb . Enter a. Dependent Variable: Number_of_people_mentioned b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .503a .253 .251 .95930 a. Predictors: (Constant), Warranty_Years ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 80.590 1 80.590 87.574 .000b Residual 237.425 258 .920 Total 318.015 259 a. Dependent Variable: Number_of_people_mentioned b. Predictors: (Constant), Warranty_Years Coefficientsa Model Unstandardized...