As reported by the College Entrance Examination Board the score on the scholasti
ID: 3200317 • Letter: A
Question
As reported by the College Entrance Examination Board the score on the scholastic Assessment Test (SAT) in 1995 was 428 points out of a possible 800. A random sample of 36 verbal scores for last year yielded a sample mean of 437.8: At the 5% significance level, does it appear that last year's mean for verbal SAT scores is greater than the 1995 mean of 428 points? Use this info for questions 32 &33. Determine the decision criteria. The critical values the separate the rejection region from the non-rejection region are z = plusminus 1.645. The critical values that separate the rejection region from the non- region are t = plusminus 1.690 The critical value the separates the rejection region from the non-rejection region is z = 1.645. The critical value the separates the rejection region from the non-rejection region is t 1.690. Determine the outcome of the hypothesis test. Reject H_o, the significance level is too small. Do not reject H_o, x is very close to H_o. Reject H_o, the value of the test statistic falls in the rejection region Do not reject H_o, the value of the test statistic falls in the non-rejection region Find the linear regression equation for the data below. y = 3.312 + 26,549x y 26.549 + 3.312x y 0.912 + 0.954x None of the above Which linear correlation coefficient is most useful for making predictions? r = 0.45 r = -0.65 r = 0.97 r = -0.15Explanation / Answer
Answer:
34).
Answer: B). y=26.549+3.312x
Regression Analysis
r²
0.911
n
15
r
0.954
k
1
Std. Error
2.174
Dep. Var.
y
ANOVA table
Source
SS
df
MS
F
p-value
Regression
627.8742
1
627.8742
132.82
3.39E-08
Residual
61.4551
13
4.7273
Total
689.3293
14
Regression output
confidence interval
variables
coefficients
std. error
t (df=13)
p-value
95% lower
95% upper
Intercept
26.549
4.6109
5.758
.0001
16.5876
36.5103
x
3.312
0.2874
11.525
3.39E-08
2.6909
3.9325
35).
Answer: c: r=0.97
Correlation with high magnitude is more useful.
Regression Analysis
r²
0.911
n
15
r
0.954
k
1
Std. Error
2.174
Dep. Var.
y
ANOVA table
Source
SS
df
MS
F
p-value
Regression
627.8742
1
627.8742
132.82
3.39E-08
Residual
61.4551
13
4.7273
Total
689.3293
14
Regression output
confidence interval
variables
coefficients
std. error
t (df=13)
p-value
95% lower
95% upper
Intercept
26.549
4.6109
5.758
.0001
16.5876
36.5103
x
3.312
0.2874
11.525
3.39E-08
2.6909
3.9325
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