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CHAPTER 16: QUANTITATIVE DATA ANALYSIS - Coggle Diagram
CHAPTER 16: QUANTITATIVE DATA ANALYSIS
Introduction
the value of data in the form of counts or numbers where each data-set has an unique numerical value associated with it. Its usually collected for statistical analysis using surveys, polls or questionnaires sent across to a specific section of a population
A variable is defined as anything that has a quantity or quality that varies. The dependent variable is the variable a researcher is interested in. An independent variable is a variable believed to affect the dependent variable
scales of measurement
ordinal scale
numerical scale
nominal scale
descriptive statistics
used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures.
univariate analysis
central tendency
: an estimate of the center of a distribution of values. (MEAN/MEDIAN/MODE)
dispersion
: the spread of the values around the central tendency.(STANDARD DEVIATION)
the distribution
: a function that shows the possible values for a variable and how often they occur.
conclusion
quantitative data analyses are the systematic recording and analysing of the data . inferential statistics are the outcomes of statistical tests, helping deduction to be made from the data collected, to test hypothesis set and related findings to the sample and population
inferential statistics
data (for example, a chart or graph) and inferential statistics allows you to make predictions (“inferences”) from that data. With inferential statistics, you take data from samples and make generalizations about a population.
the wilcoxon test for 2 paired samples
independent sample t-test
mann-whitney
chi-squared test for nominal data
pearson's correlation coefficient, r
spearman's coefficient of rank correlation