Dataset and the variables I selected.
I used the GSS2014-5.sav as the dataset. I chose two variables: the number of guns in the home and the hours usually worked weekly.
The reason why it is best to represent the data this way.
I used a simple bar chart to represent the number of people with guns in their homes. A simple bar is suitable for categorical and nominal variables, such as the different levels of variables (Frankfort Nachmias -, Leon-Guerrero & Davis, 2020).
Categorical and nominal variables
Interpretation
The X-axis in the chart below shows the respondent’s answers, and the Y-axis in the chart below shows the frequency count of the number of respondents that said Yes, No or Refused to answer about having guns in the home. For example, the majority said no to having guns in homes.
The reason why it is best to represent the data this way.
I used a simple line to represent the weekly work hours. Line charts are suitable for metric-level variables. Such as to help recognize the highest possible level of measurements in the working hours below (Frankfort Nachmias -, Leon-Guerrero & Davis, 2020).
Continuous and scale variable
Interpretation
Below, the X-axis shows the actual variable of hours usually worked a week, and the Y-axis shows the frequency. For example, forty participants worked at least 70 hours and a minimum of 15 weekly.
Descriptive Statistics |
|||||
N |
Minimum |
Maximum |
Mean |
Std. Deviation |
|
HAVE FUN AT HOME |
1711 |
1 |
3 |
1.72 |
.514 |
NUMBER OF HOURS USUALLY WORKED A WEEK |
40 |
15 |
70 |
38.70 |
12.416 |
References