COMPUTERISED QUANTITATIVE STATISTICS

Computerised Quantitative Statistics



Computerised Quantitative Statistics

Introduction

Statistical analysis is considered the tool used to answer research questions and describe different aspects about samples or populations. The use of statistical analysis should be following the statistical roles and procedures. The type of variable will determine the procedure of analysis that should be followed to describe the variable. The type of variables and its distribution will determine the type of inferential statistics that should be used.

For normally distributed continuous variable parametric analysis can be used to test the effect of independent variable on these variables. The effect testing will use non-parametric analysis in case of testing the effect of two categorical variables on each other or when testing the effect of categorical variable effect on non-normally distributed continuous variables. Reading the output of statistical analysis is considered very important as it helps in describing variables integrally. The description of variables and how they related to each other will makes it possible to understand the way these variables affect each other and so the way the questions of research will be answered.

Analyzing any database requires introducing detailed information about the variables. This requires analyzing the variables using correct procedures and relating different variables to each other. Wrong statistical procedures will lead to wrong analysis and so to wrong conclusions about the sample or population. Relying on wrong procedures will indicates wrong decision about the sample and population and will produce misleading results.

In this report British household Panel Survey data will be described applying suitable procedures for data analysis. The report will use both descriptive analysis and inferential statistics to describe the relationship among different variables or the effect of different variables on each other.

Sex Distribution

To describe the gender distribution in sample frequency and percentages were calculated for the sample. The results show that the percentage of females in sample exceeded that of males (Table 1 and Figure 1). The following information determines the fact that the distribution of males and females are almost equally distributed as there are males being 43% and 57%.

Table 1: Frequency and percentage of sex distribution

Frequency

Percent

Valid Percent

Cumulative Percent

Male

2389

43.43

43.43

43.43

Female

3112

56.57

56.57

100.00

Total

5501

100

100

Figure 1: The percentage of distribution of gender in the sample

Age Distribution

To describe the age of people in the sample, descriptive statistics was used. Means were used to determine the average age of sample. Standard deviation was used to describe the dispersion of ages from its mean. The mode was used to determine the age that is most frequent in sample. Also, minimum and maximum was used to measure the dispersion of ages in the sample. The percentiles were used to study the concentration of ages in each percentile period using percentile periods 10 intervals (Table 2 and Figure 2).

The results showed that the mean of people age is 47 indicating that the majority of people are young. On the other hand, the standard deviation shows that there is high variation of ages from mean. This indicates that there are very young people in the ...