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Lab Project: Rationale, Analysis, and Graph Assignment
Mark Smith
Statistics in Psychology
PSYC-355 D-07
Professor Jerry Green
December 6, 2021
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Attendance and Happiness
The study aims at addressing the relationship between attendance and Happiness.
The histogram is normally distributed and therefore Happiness can be a good variable to predict
Attendance and vice versa. A normal distribution is a data set design in which the majority of
values cluster around the middle of the range and the remainder taper off symmetrically to either
extreme(Ni et al. 2020).
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Attendance data has a lot of outliers and therefore would be a little bit difficult to predict .This
therefore calls for correlation analysis to analyze Pearson correlation. The aim of correlation is to
try and find out how a change in one variable would constitute to the change in another and the
significance in the change.
Correlations
Happiness
Attendance
Happiness
Pearson Correlation
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.250
Sig. (2-tailed)
.368
N
15
15
Attendance
Pearson Correlation
.250
1
Sig. (2-tailed)
.368
N
15
15
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From the correlation table we can see that the relationship coefficient between happiness and
attendance is 0.250 so a change in Happiness would change the attendance by 0.250.
To see significance in the change of any of the variables, it is important to do a regression analysis
with the dependent variable being happiness and independent variable being Attendance(Kumar
and Chong 2018).
The analysis for the regression models has been shown in the graphs below . The Histogram
indicates that the relationship between the two is normally distributed and therefore one variable
can be used to predict the other. WE can tell this from the belly shape of the two graphs.
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From the probability-Probability plot we can easily tell that an increase in the dependent variable
causes an increase in the independent. In conclusion there is a linear correlation between the two
variables .From the plot we can tell that the points are not deviating from the vertical line and
indicate a linear flow. From the graphs we can conclude that Happiness is expected to have an
effect on the attendance.
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References
Kumar, Sunil, and Ilyoung Chong. 2018. “Correlation Analysis to Identify the Effective Data in
Machine Learning: Prediction of Depressive Disorder and Emotion States.” International
Journal of Environmental Research and Public Health 15(12).
Ni, Pinghe et al. 2020. “Reliability Analysis and Design Optimization of Nonlinear Structures.”
Reliability Engineering and System Safety 198.
