In this weeksAssignment, you will differentiate between the proper use of summary statistics for categorical and continuous level data. In this exercise, you will explore what output For this Introduc

Running Head: VISUAL DISPLAY OF DATA 0

Visual display of data

Data visualization is of great help in data analysis since it gives the readers a quick understanding of what is explained in data analysis. This can be helpful since a picture sticks in the brain more compared to numbers.

In this study, we will use variables from Afrobarometer Dataset in order to check the appropriate display for various variable levels. Descriptive analysis for age (Q1) is as shown in table 1 below.

Table 1: Descriptive analysis for age

Descriptive Statistics
		Mean	Std. Deviation
Q1. Age	10232	37.39	14.86
Valid N (listwise)	10232

According to the table, the mean for ages of respondents reported was 37.39 which is approximately 37 years for the total 10,232 respondents.

Age (Q1) and Q3b. Your present living conditions, were examined and visually analyzed accordingly. Age (Q1) is a continuous variable while your present living conditions (Q3b) is categorical with 5 levels 1) Very Bad, 2) Fairly bad, 3) Neither good nor bad, 4) Fairly good and 5) Very good. Figure 1 & 2 shows the histogram for age and living conditions respectively (Wagner III W., 2020).

Figure 1: Histogram for age

In this weeksAssignment, you will differentiate between the proper use of summary statistics for categorical and continuous level data. In this exercise, you will explore what output For this Introduc 1

Figure 2: Histogram for living conditions

Looking at the histogram for age, most people who responded are between 20 and 40 years old. A few are under 20 years as seen in the histogram. The graph is skewed to the right. The histogram for living conditions displays the data for the 5 categories where 2) “Fairly bad” was the highest and 5) “Very good” was the lowest.

Social Implication

According to the analysis, most respondents reported their living conditions as fairly bad which means people living in the specified area are experiencing difficulties and needs an intervention to ensure the living standards are raised where possible. On the same, people who reported their standards as “very good” are very few.

Reference

Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.