Experiments directly influence variables, whereas descriptive and correlational studies only measure variables. It determines the statistical tests you can use to test your hypothesis later on.įirst, decide whether your research will use a descriptive, correlational, or experimental design.
Alternative hypothesis: Parental income and GPA are positively correlated in college students.Ī research design is your overall strategy for data collection and analysis.Null hypothesis: Parental income and GPA have no relationship with each other in college students.Alternative hypothesis: A 5-minute meditation exercise will improve math test scores in teenagers.Įxample: Statistical hypotheses to test a correlation.Null hypothesis: A 5-minute meditation exercise will have no effect on math test scores in teenagers.Example: Statistical hypotheses to test an effect While the null hypothesis always predicts no effect or no relationship between variables, the alternative hypothesis states your research prediction of an effect or relationship. Every research prediction is rephrased into null and alternative hypotheses that can be tested using sample data. You start with a prediction, and use statistical analysis to test that prediction.Ī statistical hypothesis is a formal way of writing a prediction about a population. The goal of research is often to investigate a relationship between variables within a population. To collect valid data for statistical analysis, you first need to specify your hypotheses and plan out your research design. Step 1: Write your hypotheses and plan your research design Frequently asked questions about statistical analysis.Test hypotheses or make estimates with inferential statistics.
Example: Causal research questionCan meditation improve exam performance in teenagers? Example: Correlational research questionIs there a relationship between parental income and college grade point average (GPA)? The first investigates a potential cause-and-effect relationship, while the second investigates a potential correlation between variables. We’ll walk you through the steps using two research examples. This article is a practical introduction to statistical analysis for students and researchers. Finally, you can interpret and generalize your findings. Then, you can use inferential statistics to formally test hypotheses and make estimates about the population. You need to specify your hypotheses and make decisions about your research design, sample size, and sampling procedure.Īfter collecting data from your sample, you can organize and summarize the data using descriptive statistics. To draw valid conclusions, statistical analysis requires careful planning from the very start of the research process. It is an important research tool used by scientists, governments, businesses, and other organizations. Statistical analysis means investigating trends, patterns, and relationships using quantitative data. The Beginner's Guide to Statistical Analysis | 5 Steps & Examples
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