Summary 6 of Presentation 6: Data Analysis – Descriptive Statistics, Inferential Statistics, and Statistics in Perspective

a)      Descriptive analysis

·         A parameter is a characteristic of a population. It is a numerical or graphic way to summarize data obtained from the population.

·         A statistic is a characteristic of a sample. It is numerical or graphic way to summarize data obtained from a sample.

·         There are two types of numerical data ;1) Quantitative data are obtained when the variable being studied is measured along a scale that indicates how much of the variable is present. It is calculated in terms of scores.

·         2)Categorical data simply indicate the total number of objects, individuals, or events a researcher finds in a particular category.

·         There are several techniques for summarizing quantitative data such as frequency polygons, skewed polygons, histograms and stem-leaf plots, the normal curve,  averages/measures of central tendency and others.

b)     Inferential Statistics

·         Are certain types of procedures that allow researcher to make inferences about a population based on findings from a sample.

·         The techniques of inferential statistics differ depending on which type of data- categorical or quantitative.

·         The term probability as used in research refers to the predicted relative frequency with which a given event will occur.

·         There are several aspects are considered in inferential statistics such as the sampling error, the distribution of sample means, confidence interval, hypothesis testing, significance levels.

·         Test of statistical significance (parametric and nonparametric tests) for both categorical data and quantitative data.

c)       Statistics in Perspective

·         To discuss the appropriate use of the descriptive and inferential statistics described in the topics above.

·         Approaches to research – a good deal of educational research is done in one of two ways, either two or more groups are compared, or variables within one group are related.

·         When comparing two or more groups using quantitative data, researchers can compare them through frequency polygons, calculation of average and calculation of spreads.

·         Other approaches to research are; relating variables within a group using quantitative data; comparing groups using categorical data; and relating variables within a group using categorical data.

·         Besides that, both parametric and nonparametric techniques should be used to analyze data rather than either one alone.

Reference:

Fraenkel J.R., & Wallen N.E.(2010). How to Design and Evaluate Research in Education, 7,183-255.