Repeating the study is possible because of standardized data collection protocols and tangible definitions of abstract concepts. Quantitative research is often used to standardize data collection and generalize findings. You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to. Using a t-test to compare the mean ratings of the two groups, you find a significant difference and support for your hypothesis. Next, you perform inferential statistics to test your hypothesis.
You find the mean (average) and the mode (most frequent rating) of procrastination of the two groups, and plot the data to see if there are any outliers. You collect data on procrastination levels of the two groups using 7-point self-rating scales.įirst, you use descriptive statistics to get a summary of the data. Examples of descriptive and inferential statisticsYou hypothesize that first-year college students procrastinate more than fourth-year college students. You can test your hypothesis or use your sample data to estimate the population parameter. Using inferential statistics, you can make predictions or generalizations based on your data. You can also use graphs, scatter plots and frequency tables to visualize your data and check for any trends or outliers. Then, you can use statistical analysis to answer your research questions.ĭescriptive statistics will give you a summary of your data and include measures of averages and variability. For example, survey and test data may need to be transformed from words to numbers. Once data is collected, you may need to process it before it can be analyzed. To assess whether attitudes towards climate change have changed since the 1980s, you collect relevant questionnaire data from widely available longitudinal studies. To study college classroom participation, you sit in on classes to observe them, counting and recording the prevalence of active and passive behaviors by students from different backgrounds.Ĭollect data that has been gathered for other purposes e.g., national surveys or historical records. Identify a behavior or occurrence of interest and monitor it in its natural setting. You distribute questionnaires with rating scales to first-year international college students to investigate their experiences of culture shock. You compare self-ratings of procrastination behaviors between the groups after the intervention.Īsk questions of a group of people in-person, over-the-phone or online. To test whether an intervention can reduce procrastination in college students, you give equal-sized groups either a procrastination intervention or a comparable task. Quantitative research methods Research methodĬontrol or manipulate an independent variable to measure its effect on a dependent variable.
To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).
The results may be generalized to broader populations based on the sampling method used.
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