Question

ANOVA df SS Regression 1 24.011 Residual 8 67.989 Coefficients Standard Error Intercept 11.065 2.043 x...

ANOVA

df

SS

Regression

1

24.011

Residual

8

67.989

Coefficients

Standard Error

Intercept

11.065

2.043

x

-0.511

0.304

a.

What has been the sample size for the above?

b.

Perform a t test and determine whether or not X and Y are related. Let α = 0.05.

c.

Perform an F test and determine whether or not X and Y are related. Let α = 0.05.
Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
ANOVA df SS Regression 1 0.72 Residual 10 62.6 Total 11 63.32 Coefficients Std Error Intercept...
ANOVA df SS Regression 1 0.72 Residual 10 62.6 Total 11 63.32 Coefficients Std Error Intercept 14.64 146.76 No. of accounts (000) 1.99 5.87 This printout is for data relating the number of ATM withdrawals (in thousands) to the number of accounts (in thousands) at that branch. Predict the number of withdrawals if the number of accounts is 24.97 thousand. State the answer in thousands correct to two decimal places.
Using the following information: Coefficients Intercept -12.8094 Independent variable 2.1794 ANOVA df SS MS F Regression...
Using the following information: Coefficients Intercept -12.8094 Independent variable 2.1794 ANOVA df SS MS F Regression 1 12323.56 12323.56 90.0481 Residual 8 1094.842 136.8550 Total 9 13418.4 The regression equation is _______. Multiple Choice Ŷ = 2.1794 − 12.8094X Ŷ = −12.8094 + 2.1794X 12.8094X = 2.1794Ŷ X = −12.8094 + 2.1794 Ŷ
Multiple R=0.81112189 R Square=0.65791872 Adj. R Square=0.61515856 Standard Error=11.6506589 Observations=10 Regression: df=1 ss=2088.497175 ms=2088.497 F=15.3863 Residual:...
Multiple R=0.81112189 R Square=0.65791872 Adj. R Square=0.61515856 Standard Error=11.6506589 Observations=10 Regression: df=1 ss=2088.497175 ms=2088.497 F=15.3863 Residual: df=8 ss=1085.902825 ms=135.7379 Total: df=9 ss=3174.4 Intercept: Coefficients=-70.39 Std. Error=30.00 P-value=0.047 X: Coefficients=17.18 Std. Error=4.38 t-stat=3.92 p value=0.004 Question: For the test of hypothesis regarding the intercept of the model, compute and report the calculated value of the test-statistic. Question: Predict value of Y, when X = 10.
df ss MS F Regression 1 15.75 15.75 8.600682594 Residual 8 14.65 1.83125 Total 9 30.4...
df ss MS F Regression 1 15.75 15.75 8.600682594 Residual 8 14.65 1.83125 Total 9 30.4 Consider the following ANOVA table obtained as part of a simple linear regression (that includes an intercept term) analysis output: . Calculate the estimated value of standard deviation of the regression model error using the above ANOVA table. Calculate the sample variance of the response/dependent variable from the above data. This is all information I have in my question
ANOVA df SS MS F Significance F Regression 849 14.04 Residual 247 Total 61 1096 Determine...
ANOVA df SS MS F Significance F Regression 849 14.04 Residual 247 Total 61 1096 Determine the degrees of freedom for the regression and degrees of freedom for the error (you may need to round to the nearest integer): Degrees of Freedom for the Regression = Degrees of Freedom for the Error =
df SS MS F Regression A 8,693.11 4,346.56 375.16 Residual 22 254.89 C Total 24 B...
df SS MS F Regression A 8,693.11 4,346.56 375.16 Residual 22 254.89 C Total 24 B Coefficients Standard Error t-stat p-value Intercept 257.74 22.82 11.29 1.27E-10 x1 -2.97 0.47 -6.31 2.37E-06 x1 0.23 0.24 0.96 0.3454 a. What is the sample regression equation? b. Interpret the slope coefficient for x1. c. Find the predicted value for y if x1 equals 25 and x2 equals 50. d. Fill in the missing values in the ANOVA table. e. Calculate the standard error...
ANOVA for SLR source df ss ms F regression 1 14.4 14.4 27 Error 3 1.6...
ANOVA for SLR source df ss ms F regression 1 14.4 14.4 27 Error 3 1.6 0.533333 Total 4 16 R^2=0.9. n=5(there are five x and five y in original table) 1.Construct a 95% confidence interval of B1(beta1),B1(beta1=-1.2) 2.Does the average value of y change with x? Assume a(alpha)=0.05 question 2 is much important plz tell me, thx
Given the following ANOVA table Source DF SS Regression 1 1800 Residual 16 900 Total 17...
Given the following ANOVA table Source DF SS Regression 1 1800 Residual 16 900 Total 17 2700 The total variability in the Y observations that can be explained by this regression model is ______%. Round to one decimal point and do not include the % sign.
Please explain me this problem without using Excel please. Thank you. df ss ms f significance...
Please explain me this problem without using Excel please. Thank you. df ss ms f significance f regression 1 552.0 552.0 69.0 0.0000 residual(error) 10 80.0 8.0 total 11 632.0 Coefficients Standard Error t Stat P-Value Intercept 4.3939 1.7569 2.5009 0.0314 X 1.9650 0.2387 8.2315 0.0000 Answer the following questions based on the above information and use a 95% confidence. a. Is the regression model significant at 95% confidence? Why or why not. Fully explain. b. Is X significant? Why...
Regression Statistics Multiple R 0.3641 R Square 0.1325 Adjusted R Square 0.1176 Standard Error 0.0834 Observations...
Regression Statistics Multiple R 0.3641 R Square 0.1325 Adjusted R Square 0.1176 Standard Error 0.0834 Observations 60 ANOVA df SS MS F Significance F Regression 1 0.0617 0.0617 8.8622 0.0042 Residual 58 0.4038 0.0070 Total 59 0.4655 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -0.0144 0.0110 -1.3062 0.1966 -0.0364 0.0077 X Variable 1 0.8554 0.2874 2.9769 0.0042 0.2802 1.4307 How do you interpret the above table?
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT