The mean is necessary to summarize that variable across all participants the standard deviation is necessary to understand how much each participant varies around that mean.Īt the moment, it is enough to calculate the mean and standard deviation and combine them all in one table. This means that all research studies must report the mean and standard deviation for all variables under study. APA standards require that researchers report descriptive statistics on the major variables under study, even for studies that will use inferential statistics, so the nature of any effect can be understood by the reader. In most cases, a total score for each variable will have been calculated in the previous step, Coding the Data. Once descriptive statistics for the personal information have been calculated, then it is time to move onto the variables under study. In the Tables and Figures page, I will describe how to convert these tables into APA format or graphically represent it in a figure. At this point, a simple table with the frequency and Percentage of personal information variables will suffice. Then take this number times 100%, resulting in 40%. To calculate the percentage of males in Table 3, take the frequency for males (80) divided by the total number in the sample (200). Percentage is calculated by taking the frequency in the category divided by the total number of participants and multiplying by 100%. How many participants out of those 100 would fall in that category? In Table 3, if there were 100 participants in the study, 55 would be female. Imagine there were exactly 100 participants in the sample. Percentages are easier to understand than frequencies because the percentage can be interpreted as follows. However, it is oftentimes difficult to interpret frequency distributions because the frequency by itself is meaningless unless there is a reference point to interpret the number. Recall that a frequency is simply the number of participants who indicated that category (aka "Male"). These are all continuous variables, so a measure of central tendency and variability should be reported to represent these variables. For example, age is on a continuum from 0 to 100 or so, academic achievement generally varies from 0 to 100, and number of pages a student reads in a week can vary from 0 to maybe 300. However, measures of central tendency and variability should be reported for variables that have continuous data, meaning that the scores can vary along a continuum of numbers. Educational qualifications can have categories of secondary school, diploma, degree, post-graduate diploma, masters, and doctorate. For example, marital status can have categories of single, married, divorced, widowed, and separated. Frequency statistics should be reported whenever the data is discrete, meaning that there are separate categories that the participant can tick. However, if participants reported their exact age, then the mean and standard deviation should be calculated for the age variable. It is up to the researcher to thoughtfully consider what the reader needs to know about the sample to make an informed decision about whether the sample is representative of the overall population.įrequency and percentage statistics should be used to represent most personal information variables. Other variables might include grade level, marital status, years of work experience, educational qualifications, socio-economic status, etc. All studies should report descriptive statistics on gender and age. The types of personal information to be included will vary depending on the type of research study. Since it is important for the reader to have a good understanding of the sample that the study was conducted on, the first statistics for all research designs should include descriptive statistics of the personal information for the sample. However, all other types of research designs will require both descriptive and inferential statistics. Measures of variability indicate the degree to which scores differ around the average.ĭescriptive research designs typically only require descriptive statistics. Measures of central tendency give one number that represents the entire set of scores, such as the mean. Frequency statistics simply count the number of times that each variable occurs, such as the number of males and females within the sample. The three main types of descriptive statistics are frequencies, measures of central tendency (also called averages), and measures of variability. Once the data has been coded and double-checked, the next step is to calculate Descriptive Statistics. Descriptive Statistics Conducting Educational Research
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