Social Research Design and Analysis: Data Analysis using SPSS

Running head: SOSC884 SOCIAL RESEARCH DESIGN & ANALYSIS 1
SOSC884 Social Research Design and Analysis
Student’s Name
Institutional Affiliation

SOSC884 SOCIAL RESEARCH DESIGN & ANALYSIS 2
Practical Exercise-Data Analysis using SPSS
PART 1 (20 Marks)
1. Four Frequency distributions and four Graphs (8 Marks)
Frequency distribution tables are important statistical tools when analyzing collected data
into an easier way that a researcher can understand. It displays the frequency that each coded
value has and its respective percentage. These tables will enable the creation of visual
representatives of the data using charts and graphs.
Nominal variables are variables with two or more groupings or categories which no specific
order. According to the data given, respondents’ sex is an example of a nominal variable since
both male and female have no intrinsic ordering. Table 1 shows that out of the 1500 respondents
that were involved in this study, 686 were male and 814 were females. This implies that 45.7%
of the sample are male respondents while 54.3%are females.
Table 1: Frequency Distribution of Respondents Sex
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid MALE 686 45.7 45.7 45.7
FEMALE 814 54.3 54.3 100.0
Total 1500 100.0 100.0
The figure 1 below represents the respondents’ sex in a pie chart. According to (Hudson, 2015),
a Pie chart usually gives a circular representation of the set data. In this chart, data is divided into
different portions that are dependent on the numerical proportion of that data. As displayed in the
frequency table, females were more males. The female slice (green) is larger compared to the
male slice (males).

SOSC884 SOCIAL RESEARCH DESIGN & ANALYSIS 3
Figure 1: Respondents Sex Pie Chart
Categorical and continuous data sets can be presented through bar, line and pie charts to
summarize and this present this data in a manner than one can easily understand.
In Ordinal variables, data variable can be ranked. These rankings are usually not equal
From the data given, Subjective Class Identification, is an example of the ordinal variable. Table
2 shows that there were 1487 valid responses out of the 1500 respondents that were involved in
this study. From this, 150(10.1%) were from the lower class, 644 (43.3%) were from working
class5, 639 (43%) were from the middle class and 54 (3.6%) were from the upper class.
Table 2: Frequency Distribution of Subjective Class Identification
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid LOWER CLASS 150 10.0 10.1 10.1
WORKING CLASS 644 42.9 43.3 53.4
MIDDLE CLASS 639 42.6 43.0 96.4
UPPER CLASS 54 3.6 3.6 100.0
Total 1487 99.1 100.0
Missing DK 10 .7
NA 3 .2
Total 13 .9
Total 1500 100.0

SOSC884 SOCIAL RESEARCH DESIGN & ANALYSIS 4
From figure 2 below, most responses were classified into the working class and middle
class respectively. Few individuals were from the upper class.
Figure 2: Subjective class Bar graph
Another example of ordinal variables is the frequency the respondents were engaged in sexual
activities the previous year. Only 904 individuals responded to this question. The remaining
individuals did not answer this question. From table 3, we can deduce that only 25 (2.8%) never
engaged in any sexual activity. Majority of the individuals have sex 2to 3 times per week
222(24.6%) with 196 (21.7%) having sex 2to 3 times a month.18.1% have sex weekly while
13.6% have it once in a month. The rest of the individuals had sex once or twice (10.5%) while
8.7% had sex more than 4 times per week.
Table 3: Frequency Distribution of Frequency of Sex during Last Year