Descriptive statistics definition and examples will be discussed in this article. The definition is a method of statistical analysis that only describe the condition of the data examples. Descriptive statistics do not draw conclusions larger than the sample. For example: Researcher conducts a research with 100 students as sample size. The conclusions drawn only for 100 students, no more. An example of a descriptive statistics in the health subject: A study measures the prevalence of TB in certain areas. It measures the effectiveness of a drugs in healing a disease. Necessarily, its conclusion only cover for that area. Other example of descriptive statistics in economic research: Average movement of stock prices on the stock exchange. The volatility of commodity price indexes on the futures exchange.
Commonly, Descriptive statistics describes a variable. Possibly, it also illustrate between two or more variables. For example, study on gender towards blood pressure in a hospital. The variable only blood pressure and gender as control variable. We may increase the number of variable such as age or life style. In political study, gender, age range, educational level to be important variable in choosing a candidate for leader in the election. Descriptive statistics does not merely involve only one variable. Two or more variables are possible. Essentially, the conclusions only cover the sample size.
Descriptive statistics is different with inferential statistics. In inferential statistics, the conclusion can be drawn beyond the sample size. For example, a research using 100 students as sample size, but the conclusion draws for whole college. Researcher want to examine the study habits of students in a college that has a total of 20 thousand students. Researchers certainly don’t need to interview 20 thousand students. It is enough to interview 100 to 300 students to get the conclusion of all college.
Descriptive VS Inferential Statistics
Inferential statistical examples in health and medicine subject: we want to examine effectiveness of anti-hypertensive drugs A compared to drugs B. It takes 50 sample size for control and 50 sample for treatment. In inferential statistics, the conclusion was not only for 100 samples but can be greater. Another example in economics: the effect of fiscal policy toward economic growth in a country. The study uses time series data samples for 5 years. In inferential statistics, conclusions can be more than 5 years or more.
Key word of inferential research is testing the hypothesis. we temporarily test the allegations of researchers by using little data or samples of the real situation. hypothesis testing is what distinguishes descriptive statistics and inferential statistics. In descriptive statistics, there is no hypothesis testing.
The similarity of descriptive and inferential statistics is both methods are quantitative method. They use statistical measurements as conclusions. Mean, median, mode and standard deviation are the statistical measurements. Merely, In a descriptive statistics, mean, median and mode and standard deviation only describes the sample size. whereas, in inferential statistics, there is a standard error which is the gap of mean median and mode in between sample and the population.
Furthermore, we discuss descriptive a statistics definition and me examples, we need to analysis the software. SPSS is a familiar tools widely used in various field of science. In the next article, it will be peeled out.