# QUANTITATIVE RESEARCH

### Description

SUMMARY OF CHAPTER 9
Flowchart by Jessica Sarabia, updated more than 1 year ago
 Created by Jessica Sarabia over 6 years ago
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## Resource summary

### Flowchart nodes

• Measures of frequency
• Measures of central tendency
• MODE
• MEDIAN
• Is the score at the center of the distribution
• It is the mist frequent score obtained by a particullar group of learners
• MEAN
• It is the arithmetic average
• Measures of dispercion
• STANDARD DERIVATION
• It is a number that shows how scores are spread around the mean
• DESCRIPTIVE STATISTICS
• QUANTITATIVE RESEARCH
• NORMAL DISTRIBUTION
• Describes the clusterings of scores/ behaviours, also known as a bell curve
• STANDARDS SCORES
• There are times when we want to compare an individual's performance on different tests.
• PROBABILITY
• It provides confidence in the claims that are being made about the analysis of the data.
• INFERENTIAL STATISTICS
• the goal is to generalize beyond the results.
• Prerequisites
• two—standard error of the mean and standard error of the difference between sample means
• Degrees of Freedom
• is the number of scores that are not fixed.
• Critical Values
• This is the value that we can use as a confidence measure to determine whether our hypothesis can be substantiated.
• One-Tailed Versus Two-Tailed Hypotheses
• The former (those that predict a difference in one direction) are known as one-tailed hypotheses and require a different critical value than do the "neutral" or two-tailed hypotheses.
• Parametric Versus Nonparametric Statistics
• Parametric Statistics
• t-tests
• Analysis of Variance (ANOVA)
• Two-way ANOVA
• Analysis of Covariance (ANCOVA).
• Multivariate Analysis of Variance (MANOVA)
• Repeated Measures ANOVA
• Nonparametric Tests
• Chi Square (X2)
• Mann-Whitney U/Wilcoxon Rank Sums
• Kruskal-Wallis/Friedman
• STATISTICAL TABLES
• tables that can be consulted to determine if your test results are significant
• STRENGTH OF ASSOCIATION
• There are times when we might want to determine how much of the variation is actually due to the independent variable in question
• ETA2 AND OMEGA2
• goes beyond the fact that there is a significant difference and gives us an indication of how much of the variability is due to our independent variable
• EFFECT SIZE
• It is a measure that gives an indication of the strength of one's findings.
• META-ANALYSES
• To make a meaningful comparison, effect sizes become the main comparative tool.
• ORRELATION
• Correlational research attempts to determine the relationship between or among variables; it does not determine causation.

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Thick Desrcription
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