A social psychologist hypothesizes that the more initial
attraction a person has to another predicts more anxiety before
their first date. Below are the first date data from a sample of
participants. What can the psychologist conclude with an α of
0.01?
Attraction | Anxiety |
---|---|
2 6 1 3 6 9 6 6 3 |
8 11 5 8 10 11 8 8 7 |
a) What is the appropriate statistic?
Slope
Chi-Square
Compute the statistic selected above:
Appropriate statistic- slope
X | Y | XY | X² | Y² |
2 | 8 | 16 | 4 | 64 |
6 | 11 | 66 | 36 | 121 |
1 | 5 | 5 | 1 | 25 |
3 | 8 | 24 | 9 | 64 |
6 | 10 | 60 | 36 | 100 |
9 | 11 | 99 | 81 | 121 |
6 | 8 | 48 | 36 | 64 |
6 | 8 | 48 | 36 | 64 |
3 | 7 | 21 | 9 | 49 |
Ʃx = | Ʃy = | Ʃxy = | Ʃx² = | Ʃy² = |
42 | 76 | 387 | 248 | 672 |
Sample size, n = | 9 |
x̅ = Ʃx/n = 42/9 = | 4.66666667 |
y̅ = Ʃy/n = 76/9 = | 8.44444444 |
SSxx = Ʃx² - (Ʃx)²/n = 248 - (42)²/9 = | 52 |
SSyy = Ʃy² - (Ʃy)²/n = 672 - (76)²/9 = | 30.2222222 |
SSxy = Ʃxy - (Ʃx)(Ʃy)/n = 387 - (42)(76)/9 = | 32.3333333 |
Slope, b = SSxy/SSxx = 32.33333/52 = 0.6217949
y-intercept, a = y̅ -b* x̅ = 8.44444 - (0.62179)*4.66667 = 5.542735
Regression equation :
ŷ = 5.5427 + (0.6218) x
Sum of Square error, SSE = SSyy -SSxy²/SSxx = 30.22222 - (32.33333)²/52 = 10.1175214
Standard error, se = √(SSE/(n-2)) = √(10.11752/(9-2)) = 1.20223
Standard error for slope, se(b1) = se/√SSxx = 1.20223/√52 = 0.16672
Slope Hypothesis test:
Null and alternative hypothesis:
Ho: β₁ = 0 ; Ha: β₁ > 0
Test statistic:
t = b/(seb1) = 3.7296
df = n-2 = 7
p-value = T.DIST.2T(ABS(3.7296), 7) = 0.0037
Conclusion:
p-value < α Reject the null hypothesis.
There is enough evidence to conclude that there is a positive relationship between the two variables.
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