Question

23. Suppose the classes for an organized set of data are as follows: please fill in...

23. Suppose the classes for an organized set of data are as follows: please fill in the A column and answer B and C.

Class

A.

B.

C.

Mid-Point

What is the value of class width?

Into which class is the value 1.515 assigned?

0.235 – 0.875

0.875 – 1.515

1.515 – 2.155

24.Please fill in the blank and answer the following questions:

SUMMARY OUTPUT

Regression Statistics

Multiple R

__________

R Square

__________

Adjusted R Square

0.125

Standard Error

__________

Observations

__________

ANOVA

df

SS

MS

F

Significance F

Regression

1

0.828

__________

__________

0.2308

Residual

__________

2.227

__________

Total

6

__________

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

112.413

9.484

11.853

7.52722E-05

88.033

136.793

_____

__________

X

-19.137

14.033

-1.364

0.231

-55.211

16.937

___

__________

What is the coefficient of determination?

What is the coefficient of correlation?

Interpret the coefficient of determination

Interpret the coefficient of correlation

Homework Answers

Answer #1

23)

Mid point = (Lower Limit + Upper limit)/2

Class Width = Upper Limit – Lower Limit = 0.875 – 0.235 = 0.64

24)

For ANOVA Table:

Df Residual = df Total – df Regression

MS Regression = SS Regression / df Regression

MS Residual = SS Residual / df Residual

F = MS Regression/ MS Residual

SS Total = SS Regression + SS Residual

Completed Tables:

For Regression Summary,

R Square = SS Regression / SS Total

Multiple R = - Sqrt(R Square)

Standard Error = Sqrt(MS Residual)

Observations = df Total + 1

Coefficient of determination is 0.271. It means than 27% of the variation in the dependent variable is explained by the independent variable.


Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Discuss the model and interpret the results: report overall model fit (t and significance), report the...
Discuss the model and interpret the results: report overall model fit (t and significance), report the slope coefficient and significance, report and interpret r squared. Regression Statistics Multiple R 0.001989374 R Square 3.95761E-06 Adjusted R Square -0.005046527 Standard Error 8605.170404 Observations 200 ANOVA df SS MS F Significance F Regression 1 58025.4985 58025.4985 0.00078361 0.977695901 Residual 198 14661693620 74048957.68 Total 199 14661751645 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 15668.85874 2390.079111 6.555790838...
3. United Park City Properties real estate investment firm took a random sample of five condominium...
3. United Park City Properties real estate investment firm took a random sample of five condominium units that recently sold in the city. The sales prices Y (in thousands of dollars) and the areas X (in hundreds of square feet) for each unit are as follows         Y= Sales Price ( * $1000) 36 80 44 55 35 X = Area (square feet) (*100) 9 15 10 11 10 a. The owner wants to forecast sales on the basis of...
Compare the two regression models. Does it make sense that spending and household debt could each...
Compare the two regression models. Does it make sense that spending and household debt could each be predicted by annual household income? Why or why not? 1. Predicting spending by household income Regression Statistics Multiple R 0.859343186 R Square 0.738470711 Adjusted R Square 0.737149856 Standard Error 1602.157625 Observations 200 ANOVA df SS MS F Significance F Regression 1 1435121315 1435121315 559.085376 1.42115E-59 Residual 198 508247993.2 2566909.056 Total 199 1943369308 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower...
interpret each coefficient estimate and discuss its significance using α = 0.01, α = 0.05 and...
interpret each coefficient estimate and discuss its significance using α = 0.01, α = 0.05 and α = 0.10. Use the concepts of strict and weak significance too SUMMARY OUTPUT Regression Statistics Multiple R 0.820140129 R Square 0.672629832 Adjusted R Square 0.658699186 Standard Error 235.4076294 Observations 50 ANOVA df SS MS F Significance F Regression 2 5351505.158 2675752.58 48.2841827 4.0125E-12 Residual 47 2604587.342 55416.752 Total 49 7956092.5 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper...
Using this regression model below that I created to, interpret the slope estimates, that is interpret...
Using this regression model below that I created to, interpret the slope estimates, that is interpret the impact that income [per capita gross national income] has on U5MR [No. of deaths of children 0-5 years old, per 1000 live births]. Then interpret the r square [for example what % of the variation can be explained by the other variable]. Lastly calculate the predicted values of U5MR when income = $10,000. Regression Statistics Multiple R 0.443388 R Square 0.196593 Adj R...
Can weight of a vehicle significantly predict fuel economy? How can you tell? (Include statistic and...
Can weight of a vehicle significantly predict fuel economy? How can you tell? (Include statistic and level of significance/p value) Write an APA statement with the findings from this regression analysis. Regression Statistics Multiple R 0.045643559 R Square 0.002083334 Adjusted R Square -0.05335648 Standard Error 10.03995374 Observations 20 ANOVA df SS MS F Significance F Regression 1 3.78791868 3.78791868 0.037578 0.848463 Residual 18 1814.41208 100.800671 Total 19 1818.2 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0%...
f. Interpret the slope coefficient for one of the dummy variables included in your regression model....
f. Interpret the slope coefficient for one of the dummy variables included in your regression model. g. For the slope coefficient of the variable with the smallest slope coefficient (ignore sign, use absolute value), test to see if the “a priori” expectation from part (a) is confirmed. Use alpha = 0.05. h. Interpret the coefficient of determination in this situation. i. Test the explanatory power of the entire regression model. Please use alpha = 0.01. j. For the variable with...
Use the regression model I created below for U5MR [No. of deaths of children 0-5 yrs...
Use the regression model I created below for U5MR [No. of deaths of children 0-5 yrs old per 1000 live births] and Female Youth LR [Percent of females 15-24 literate] to answer this question. Interpret the slope estimates that is interpret the impact Female Youth LR has on U5MR, then interpret the r square for example what % of what variation can be explained by what variable. Lastly calculate the predicted values U5MR when Female Youth LR= 80. Regression Statistics...
Identify and interpret the F test (one paragraph): Using the p-value approach, is the null hypothesis...
Identify and interpret the F test (one paragraph): Using the p-value approach, is the null hypothesis for the F test rejected or not rejected? Why or why not? Interpret the implications of these findings for the model. SUMMARY OUTPUT Regression Statistics Multiple R 0.60 R Square 0.36 Adjusted R Square 0.26 Standard Error 9.25 Observations 30.00 ANOVA df SS MS F Significance F Regression 4.00 1212.46 303.12 3.54 0.02 Residual 25.00 2139.14 85.57 Total 29.00 3351.60 Coefficients Standard Error t...
SUMMARY OUTPUT Regression Statistics Multiple R 0.84508179 R Square 0.714163232 Adjusted R Square 0.704942691 Standard Error...
SUMMARY OUTPUT Regression Statistics Multiple R 0.84508179 R Square 0.714163232 Adjusted R Square 0.704942691 Standard Error 9.187149383 Observations 33 ANOVA df SS MS F Significance F Regression 1 6537.363661 6537.363661 77.4535073 6.17395E-10 Residual 31 2616.515127 84.40371378 Total 32 9153.878788 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 61.07492285 3.406335763 17.92980114 6.41286E-18 54.12765526 68.02219044 54.12765526 68.02219044 Time (Y) -0.038369095 0.004359744 -8.800767426 6.17395E-10 -0.047260852 -0.029477338 -0.047260852 -0.029477338 Using your highlighted cells, what is the equation...