if R2 = -1.-00 in a regression analysis, what is the residual error? a. -1 b....
if R2 = -1.-00 in a regression analysis, what is the residual error?
a. -1
b. 0
c. 100%
d. +1
e. minus infinity
Homework Answers
the question not true
becouse the R2 is lies betwwen 0 to 1
R2 means coefficient of determination and always >=0 becouse R2 is squre of the correlation coefficient
if R2 =1 in a regression analysis the residual error is
b. 0
if R2 =0 in a regression analysis the residual error is
d. +1
if R2 =100% in a regression analysis the residual error is
b. 0%
if R2 =0% in a regression analysis the residual error is
c. 100%
Add Answer to:
if R2 = -1.-00 in a regression analysis, what is the
residual error?
a. -1
b....
In a regression analysis, if r2 = 1, then Select one: a. SSR = SST. b....
In a regression analysis, if r2 = 1, then Select one: a. SSR = SST. b. SSE = SST. c. SSR = SSE. d. SSE = 1.
In multiple regression analysis, which one of the following is the appropriate notation for error (residual)?...
In multiple regression analysis, which one of the following is the appropriate notation for error (residual)? O None of these answers is correct y-y
In regression, what is the best description of a residual? a. the predicted values b. the...
In regression, what is the best description of a residual? a. the predicted values b. the square of actual values c. the sum of the squared difference between the predicted and actual values d. error
#1 In simple linear regression, r is the: a) coefficient of determination. b) mean square error. ...
#1 In simple linear regression, r is the: a) coefficient of determination. b) mean square error. c) correlation coefficient. d) squared residual. #2 In regression analysis, with the model in the form y = β0 + β1x + ε, x is the a) estimated regression equation. b) y-intercept. c) slope. d) independent variable. #3 A regression analysis between sales (y in $1,000s) and advertising (x in dollars) resulted in the following equation. ŷ = 40,000 + 3x The above equation...
In simple regression analysis the quantity that gives the amount by which...
17. In simple regression analysis the quantity that gives the amount by which Y (dependent variable) changes for a unit change in X (independent variable) is called theA. Coefficient of determinationB. Slope of the regression lineC. Y intercept of the regression lineD. Correlation coefficientE. Standard error18. A simple regression analysis with 20 observations would yield ________ degrees of freedom error and _________ degrees of freedom total.A. 1, 20B. 18,19C. 19, 20D. 1, 19E. 18, 2019. The correlation coefficient may assume...
& a Question 10 (2 points) In a good regression model the residual plot shows an...
& a Question 10 (2 points) In a good regression model the residual plot shows an increasing pattern an arched pattern a cone pattern a random pattern a decreasing pattern Question 11 (1 point) In regression analysis, error equals predicted value minus actual value. True False
How do we come out with the std.error. #3-ANOVA with solutions Regression Analysis R2 0.642 20...
How do we come out with the std.error.
#3-ANOVA with solutions Regression Analysis R2 0.642 20 R 0.801 Std. Error 3.219 ANOVA table MS 157.9645 10.3605 df p-value Source Regression Residual Total 315.9291 176.1284 492.0575 15.25 0002 17 19 Regression output Variables Intercept Months Gender Coefficients 15.7625 0.4415 3.8598 std. error 3.0782 0.0839 1.4724 5.121 5.263 2.621 p-value 0001 0001 0179
1st regression analysis 2nd regression analysis 1. Analyze the two regression analysis's above ...
1st regression analysis
2nd regression analysis
1. Analyze the two regression analysis's above and make
a recommendation on if the organization should increase, decrease,
or retain their pricing and why?
2. What happens to the dependent variable Y if the price
X1 decreases in the second regression analysis?
SUMMARY OUTPUT Y=UNITS SOLD X=PRICE Regression Statistics Multiple R R Square Adiusted R S Standard Error Observations 0.874493978 0.764739718 0.756026374 159.2178137 29 quare ANOVA df MS Significance F 1 2224908.261 2224908.26187.76650338 5.64792E-10...
Regression Analysis 2 You run a regression analysis and receive the following results SUMMARY OUTPUT Regression...
Regression Analysis 2 You run a regression analysis and receive the following results SUMMARY OUTPUT Regression Statistics Multiple R 0 .9697622171 R Square 0.940438758 Adjusted R Square 0.92058501 Standard Error 360.0073099 Observations 5 IIIIIIII ANOVAT di SS M S F Sanificance Regression 11 6 139184 2116139184 2111 47 368327870 000 Residual 3 3 88.815.78951129605,26321 Total 146528000T IUSTI Intercept X Variable 1 Coefficients 2056. 58 1.50 Standard Error 4 54.25 0.1816 Stat 6.728812231 .882465029 P-value 0006701290 0.006283174 Refer to the Regression...
J. Thie uala set is 1or b4 banks. R2 Std. Error 6.977 0.519 64 ANOVA table Source df MS F p-value 1 3,260.0981 66.97 1.90E-11 62 3,260.0981 3,018.3339 Regression Residual 48.6828 Total 6,278.4320...
J. Thie uala set is 1or b4 banks. R2 Std. Error 6.977 0.519 64 ANOVA table Source df MS F p-value 1 3,260.0981 66.97 1.90E-11 62 3,260.0981 3,018.3339 Regression Residual 48.6828 Total 6,278.4320 63 Regression output Confidence Interval Lower 95% Upper 95% variables Coefficients Std. Error tStt p-value Intercept 65763 1.9254 3.416 0011 2.727510.4252 X1 00452 0.0055 8.183 1.90E-11 0.0342 0.0563 Calculate the R2 a. b. In words what does the R? say about total revenue for a bank? c....
In multiple regression analysis, which one of the following is the appropriate notation for error (residual)? O None of these answers is correct y-y
& a Question 10 (2 points) In a good regression model the residual plot shows an increasing pattern an arched pattern a cone pattern a random pattern a decreasing pattern Question 11 (1 point) In regression analysis, error equals predicted value minus actual value. True False
How do we come out with the std.error.
#3-ANOVA with solutions Regression Analysis R2 0.642 20 R 0.801 Std. Error 3.219 ANOVA table MS 157.9645 10.3605 df p-value Source Regression Residual Total 315.9291 176.1284 492.0575 15.25 0002 17 19 Regression output Variables Intercept Months Gender Coefficients 15.7625 0.4415 3.8598 std. error 3.0782 0.0839 1.4724 5.121 5.263 2.621 p-value 0001 0001 0179
1st regression analysis
2nd regression analysis
1. Analyze the two regression analysis's above and make
a recommendation on if the organization should increase, decrease,
or retain their pricing and why?
2. What happens to the dependent variable Y if the price
X1 decreases in the second regression analysis?
SUMMARY OUTPUT Y=UNITS SOLD X=PRICE Regression Statistics Multiple R R Square Adiusted R S Standard Error Observations 0.874493978 0.764739718 0.756026374 159.2178137 29 quare ANOVA df MS Significance F 1 2224908.261 2224908.26187.76650338 5.64792E-10...
Regression Analysis 2 You run a regression analysis and receive the following results SUMMARY OUTPUT Regression Statistics Multiple R 0 .9697622171 R Square 0.940438758 Adjusted R Square 0.92058501 Standard Error 360.0073099 Observations 5 IIIIIIII ANOVAT di SS M S F Sanificance Regression 11 6 139184 2116139184 2111 47 368327870 000 Residual 3 3 88.815.78951129605,26321 Total 146528000T IUSTI Intercept X Variable 1 Coefficients 2056. 58 1.50 Standard Error 4 54.25 0.1816 Stat 6.728812231 .882465029 P-value 0006701290 0.006283174 Refer to the Regression...
J. Thie uala set is 1or b4 banks. R2 Std. Error 6.977 0.519 64 ANOVA table Source df MS F p-value 1 3,260.0981 66.97 1.90E-11 62 3,260.0981 3,018.3339 Regression Residual 48.6828 Total 6,278.4320 63 Regression output Confidence Interval Lower 95% Upper 95% variables Coefficients Std. Error tStt p-value Intercept 65763 1.9254 3.416 0011 2.727510.4252 X1 00452 0.0055 8.183 1.90E-11 0.0342 0.0563 Calculate the R2 a. b. In words what does the R? say about total revenue for a bank? c....
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