Social research methods Essay Example | Topics and Well Written Essays - 1500 words - 2

Social research methods - Essay Example Different types of statistics can be used to serve different purposes of the research. While descriptive statistics can be used to describe the data, statistical model can be used to forecast data. Researches that are aimed at finding relationship between variables can make use of statistical techniques such as correlation and regression. Difference between Descriptive and Inferential statistics, purpose of each and applications Descriptive statistics: Descriptive statistics can be defined as the set of tools and techniques that can be used to describe the quantitative features of a collection of data (Mann, 1995). The main purpose of using descriptive statistics is to summarize a data set. Statistics such as measures of central tendency, measures of variation, graphs, and bar charts etc are examples of descriptive statistics. The three most important types of descriptive statistics are: measures of central tendency, dispersion and distribution. While distribution is an indication of the frequency of specific values of a range of data variables, measures of central tendency such as mean and median are aimed at finding the center of the entire data set (Levin and Rubin, 2007). Measures of dispersions such as range or standard deviation are an indication of the spread of data set. Inferential statistics: Inferential statistics are the set of tools and techniques that can be used to draw inferences about a population from a small sample of data (Lane, 2011). The various examples of inferential statistics techniques include t-test, Analysis of Variance, Correlation analysis, regression analysis, factor and cluster analysis and discriminant function analysis etc. There are two types of inferential statistics: estimation testing and hypothesis testing. While in estimation testing, the confidence interval of a particular parameter is calculated using the sample, hypothesis testing is generally used to compare certain parameters in two or more samples or comparing a sa mple parameter to a specific value. A hypothesis can be defined as an assumption about a population parameter (Stattrek, 2011). The null hypothesis can be defined as the hypothesis of no difference or the hypothesis of status quo (Bajpai, 2009). The alternate possibility is called the alternate hypothesis. Hypothesis testing can be used by researchers to test certain theories that they want to prove. Frequency table and bar chart a. Ethnic origin Ethnic origin (5 groups) Frequency Percent Valid Percent Cumulative Percent Valid White 3746 91.1 91.5 91.5 Mixed race 35 .9 .9 92.3 Asian 179 4.4 4.4 96.7 Black 87 2.1 2.1 98.8 Other 48 1.2 1.2 100.0 Total 4095 99.6 100.0 Missing -8 16 .4 Total 4111 100.0 Table 1: Frequency table for ethnic origin As can be seen from the frequency table, the most common ethnic group is White. The next highest frequency of ethnic group is Asian with 4.4% of the data items. Another way of representing the data is using a bar chart. The graph below shows the bar chart for the data set: Figure 1: Bar chart for ethnic origin b. Education level The frequency table for the variable education level is shown below: Education Level - 2000 Frequency Percent Valid Percent Cumulative Percent Valid Higher Degree 147 3.6 4.6 4.6 First Degree 450 10.9 14.0 18.6 Teaching qualification 47 1.1 1.5 20.0 Other higher qualification