Data Analysis
Data Analysis
Before analysis, the data should be organized by assigning numerical scores to the data and determining the categories for those scores. Once the data is in numerical form, statistical analysis is used to investigate the relationship or difference between the variables to draw conclusions related to the research questions. Statistical analysis can be categorized into two main types, which are descriptive statistics and inferential statistics.
A descriptive statistic is used to summarize the samples and measurement in order to examine the key features of the data. It include three main components:
Distribution - Shows how often each value occurs in a dataset
Central tendency - Describes the center point of data using the mean, median or mode
Variability - Indicates how spread out the values are using standard deviation, variance, minimum and maximum values, kurtosis and skewness
A inferential statistic is used to predict and draw conclusion from a larger population based on sample data. Random sampling and unbiased procedures are crucial to ensure validity and generalizability of the findings from the sample to the population.
Ghanad, A. (2023). An overview of quantitative research methods. International Journal of Multidisciplinary Research and Analysis, 6(8), 3794–3803. https://doi.org/10.47191/ijmra/v6-i8-52