statistical analysis in quantitative research

resproj

descriptive statistics

quantitatively or visually summarizes the features of a sample

univariate descriptive statistics

used to describe data containing only one variable

ungrouped data

raw data obtained

grouped data

data that is organized logically

measures of central tendency

describes data by determining a single representative central value

percentage

any proportion from the whole

standard deviation

shows the spread of data around the mean

median

the center-most observation obtained by arranging the data in ascending order

mode

most frequently occurring observation in the data set

measures of dispersion

determines how spread out a distribution is with respect to the central value

range

the difference between the highest and lowest value

variance

the variability of the distribution with respect to the mean

inferential statistics

used to draw inferences about the population data from the sample data by making use of analytical tools

correlation analysis

estimates the strength of a relationship between two quantitative variables

regression analysis

explains the relationship between dependent and independent variables

hypothesis testing

determines quantity under a given assumption

p-value

the probability of obtaining the observed results if the null hypothesis were true

type I error

rejecting the null hypothesis when it’s true

type II error

accepting/ not rejecting the null hypothesis when it’s false

critical value approach

determines whether the observed test statistics is more extreme than a defined critical value

analysis of variance

comparing the means of three or more groups to determine if there is a statistically significant difference between them

chi-square test

determines if there’s a significant relationship between two categorical variables by comparing observed frequencies with expected frequencies

estimation

using a sample statistic to estimate a population parameter