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Quantitative Data Analysis Inforgraphics Quantitative Data Analysis 2429 systematic approach to' investigations during which numerical data research which inVolves is collected measuring or counting attributes Sourses of Quantitative Data Interview Questionnaire Observation Archive Database 2 What we can do to quantitative data? How can we represent data? as graphical displays as summary statistics Organize them as tables summarize them do exploratory analysis Main Issues in Quantitative Data Analysis: Hypotheses Causality Generalisability Reliability (external Validity) (internal validity) Methods of Analyzing Data: 1. Numerical counts or frequences tell us how many times something occured or how many responses fit into a particular category; serve as a base for other calculations 1234567 2. Percentages express information as a proportion of a whole; easy to interpret; good way to show relationships and comparisons; useful when wwe want to show a frequency distribution Of grouped data 3. Measures of central tendency are used to characterize what is typical for the group; allow us to visualize or identify the central characteristic or the representative unit Mode- LMean Median Mode Mean Median the most Commonly occuring answer or Value is obtained by summing all the answers or scores and deviding by the total number the middle Value 4. Measure of variability expresses the spread or variation in responses; 1ooking at variability often provides a better understanding of the results Range Standard Variance Compares the highest and lowest Value to indicate the spread of responses or SCores the square of the standard deviation Deviation measures the degree to which individual Values Vary from the mean Created by Infographic Design Services .com Sources:

Quantitative Data Analysis Inforgraphics

shared by elizabethjones on Dec 10
infographic about quantitative data anylysis, it's essence, sources, methods of analysis, main issues, and other interesting facts on this topic


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