1. This data set contains simulated scores based on the results of Carolyn Aibel's Ph.D. thesis, albeit greatly
simplified compared to her design. The objective of this study is to observe the psychological effect of
one pound weight gain versus one pound of weight loss. We have designed several tests to observe and
test our hypothesis.

2. 1.0 Correlation Test
This test examines relationships between imagined weight gain and the changes in the confidence
level (GES_gain) also between imagined weight loss and the changes in the confidence level
(GES_loss).
Correlations
GES: Imagined
Loss
Change in lbs:
Loss
GES: Imagined Loss Pearson Correlation 1 .176*
Sig. (2-tailed) .013
N 200 200
Change in lbs: Loss Pearson Correlation .176*
1
Sig. (2-tailed) .013
N 200 200
*. Correlation is significant at the 0.05 level (2-tailed).
Relationship between Confidence Level and Imagined Weight Loss
The results revealed significant and positive relationship (r=0.176, N=200, p<0.05).The correlation’s
strength was almost absent. Loss in weight was associated with increased in confidence level
(GES_loss)

3. Correlations
Change in lbs:
Gain
GES: Imagined
Gain
Change in lbs: Gain Pearson Correlation 1 -.229**
Sig. (2-tailed) .001
N 200 200
GES: Imagined Gain Pearson Correlation -.229**
1
Sig. (2-tailed) .001
N 200 200
**. Correlation is significant at the 0.01 level (2-tailed).
Relationship between Confidence Level and Imagined Weight Gain
The results revealed significant and negative relationship (r= -0.229, N=200, p<0.05).The correlation
was very weak in strength. Gain in weight was associated with reduced in confidence level
(GES_gain).

4. Independent samples t-test is carry out to compare the mean score on both on GES_loss and GES_gain
for male and female.
The results are as follow:
1. For GES_loss:
Group Statistics
Gender N Mean Std. Deviation Std. Error Mean
GES: Imagined Loss Male 86 94.3340 36.33466 3.91807
Female 114 93.1728 32.74454 3.06681
Independent Samples Test
Levene's Test for Equality of
Variances
F Sig. t df Sig.
GES: Imagined Loss Equal variances assumed .888 .347 .237 198
Equal variances not assumed .233 172.386
For the above data, since the p-value for Levene’s Test is larger than 0.05, which is 0.35, it shows no
significant difference between the variances. So,it fit the assumption for t-test,which is equality of
variances.
For the p-value for the t-test,since it is larger than 0.05,which is 0.81, it shows no significant difference
between GES_loss for male and female.
2. For GES_gain:
Group Statistics
Gender N Mean Std. Deviation Std. Error Mean
GES: Imagined Gain Male 86 22.8082 46.79397 5.04592
Female 114 27.8398 47.62628 4.46061

5. Independent Samples Test
Levene's Test for Equality of
Variances
F Sig. t df Sig.
GES: Imagined Gain Equal variances assumed .060 .807 -.745 198
Equal variances not assumed -.747 184.845
For the above data, since the p-value for Levene’s Test is larger than 0.05, which is 0.81, it shows no
significant difference between the variances. So, it fit the assumption for t-test, which is equality of
variances.
For the p-value for the t-test,since it is larger than 0.05,which is 0.46, it shows no significant difference
between GES_gain for male and female.

6. Independent Samples Test
Levene's Test for Equality of
Variances
F Sig. t df Sig.
GES: Imagined Gain Equal variances assumed .060 .807 -.745 198
Equal variances not assumed -.747 184.845
For the above data, since the p-value for Levene’s Test is larger than 0.05, which is 0.81, it shows no
significant difference between the variances. So, it fit the assumption for t-test, which is equality of
variances.
For the p-value for the t-test,since it is larger than 0.05,which is 0.46, it shows no significant difference
between GES_gain for male and female.