Session Long Project
The
purpose of this paper is to examine predictors for the number of weekly hours
spent using email through analyzing descriptive statistics, correlation and
bivariate analysis, checking assumptions, and performing linear and multiple
regression.
Methodology
There are
six variables in the data set. First, ID represents the ID number of a
respondent. Second, AGE denotes the age of a respondent. Third, CHILDREN represent
the number of children a respondent has. Four, SEX represents the sex of a
responder. Five, EMAILHR signifies how many hours per week a respondent uses
their email. Six, INCOME embodies the total family income. Out of these six
variables, EMAILHR is the dependent variable, and the others are independent
variables. Table 1 summarizes the variables in this study, providing the name
of the variable, whether the variable is a dependent one or independent, and
the type of the variable, such as categorical, ordinal, or continuous.
Table 1
Variables Used in the Study
Variable |
Dependency |
Type |
Respondent ID number |
IV |
Categorical (Nominal) |
Age of respondent |
IV |
Numerical (Discrete) |
Number of children |
IV |
Numerical (Discrete) |
Respondents sex |
IV |
Categorical (Nominal) |
Email hours per week |
DV |
Numerical (Continuous) |
Total family income |
IV |
Categorical (Ordinal) |
Descriptive Statistics
The age
variable ranges from 20 to 76 years
old. The mean age of the respondents is 45.13 years old, whereas the median age
is 43.00 years old. This tendency indicates that
the distribution of data is skewed to the right because it is typical for
right-skewed data to have the median smaller than the mean. In other words, the
sample tends to have slightly more younger respondents than older ones. The
standard deviation for the AGE variable is 14.571, which implies there is a considerable variation among the
respondents in their age.
The
number of children ranges from 0 to
7. The mean the number of children is 1.69 children per respondent, whereas the
median number of children is 2.00 children. Although the mean is less than the
median, the data is undoubtedly right skewed. This conclusion is because many
individuals do not have children at all, and in the modern world, families
rarely have more than two children. The standard deviation, SD = 1.638, also proves
that there is a wide variety among the respondents.
The
sample (n = 87) has 46 women and 41
men. Consequently, females make up 52.87 percent of the sample, and males make
up 47.13 percent. As for the level of income, most respondents (71.26 percent)
earn $25,000 or more per year, and only 28.74 percent make between $1,000 –
$24,999.
The
weekly hours spent using email range from 0 hours to 60 hours. The mean number
of hours is 8.78 hours per week, whereas the median is only 2.00 hours weekly. This
enormous difference between the mean and median suggests that the data is
skewed to the right. Indeed, the most common value in the EMAILHR variable is
0, which means many individuals do not use emails at all. The standard
deviation is 13.885, which is even higher than the mean.
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