SUMMARY OUTPUT Regression Statistics Multiple R 0.175383 R Square 0.030759 Adjus
ID: 3227022 • Letter: S
Question
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.175383
R Square
0.030759
Adjusted R Square
-0.0904
Standard Error
3.628472
Observations
10
ANOVA
df
SS
MS
F
Significance F
Regression
1
3.342553
3.342553
0.253881
0.627935
Residual
8
105.3264
13.16581
Total
9
108.669
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
17.20206
2.452348
7.014526
0.000111
11.54693
22.85718
11.54693
22.85718
X Variable 1
-0.21413
0.424972
-0.50387
0.627935
-1.19412
0.765857
-1.19412
0.765857
What is the regression line equation?
What is the p-value?
Would you accept or reject the null?
What does this mean?
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.175383
R Square
0.030759
Adjusted R Square
-0.0904
Standard Error
3.628472
Observations
10
ANOVA
df
SS
MS
F
Significance F
Regression
1
3.342553
3.342553
0.253881
0.627935
Residual
8
105.3264
13.16581
Total
9
108.669
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
17.20206
2.452348
7.014526
0.000111
11.54693
22.85718
11.54693
22.85718
X Variable 1
-0.21413
0.424972
-0.50387
0.627935
-1.19412
0.765857
-1.19412
0.765857
Explanation / Answer
Answer:
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.175383
R Square
0.030759
Adjusted R Square
-0.0904
Standard Error
3.628472
Observations
10
ANOVA
df
SS
MS
F
Significance F
Regression
1
3.342553
3.342553
0.253881
0.627935
Residual
8
105.3264
13.16581
Total
9
108.669
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
17.20206
2.452348
7.014526
0.000111
11.54693
22.85718
11.54693
22.85718
X Variable 1
-0.21413
0.424972
-0.50387
0.627935
-1.19412
0.765857
-1.19412
0.765857
What is the regression line equation?
Y=17.20206 - 0.21413 x
What is the p-value?
P=0.627935
Would you accept or reject the null?
We accept the null hypothesis ( calculated P=0.627935 which is > 0.05 level of significance.)
What does this mean?
The variable x is not significantly predicting y. ( there is no significant linear relation between x and y).
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.175383
R Square
0.030759
Adjusted R Square
-0.0904
Standard Error
3.628472
Observations
10
ANOVA
df
SS
MS
F
Significance F
Regression
1
3.342553
3.342553
0.253881
0.627935
Residual
8
105.3264
13.16581
Total
9
108.669
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
17.20206
2.452348
7.014526
0.000111
11.54693
22.85718
11.54693
22.85718
X Variable 1
-0.21413
0.424972
-0.50387
0.627935
-1.19412
0.765857
-1.19412
0.765857
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