DATA ANALYSIS. QEM Network HBCUUP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. Howard University


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1 DATA ANALYSIS QEM Network HBCUUP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. Howard University
2 Quantitative Research
3 What is Statistics? Statistics (as a subject) is the science which provides a body of principles methodologies for designing the process of collecting the data, summarizing and interpreting the data, and drawing conclusions and inferences.
4 Types of Statistics Descriptive Statistics Descriptive statistics are used to organize and summarize observations Inferential Statistics Inferential statistics are used to draw inferences about the conditions that exist in a population from study of a sample drawn from that population
5 Types of Statistics Descriptive Statistics Measures of central tendency Mean, median, mode Measures of variability Range, variance, standard deviation, semiinterquartile range Inferential Statistics Parametric Tests ttests, Analysis of variance (ANOVA) Nonparametric Tests ChiSquare test; the sign test
6 Inferential Statistics Types of hypotheses Research hypothesis Null hypothesis Tests of the null hypothesis among Relationships Means Proportions
7 Correlational Techniques Correlation: A measure of the degree of association between two or more variables. Pearson s correlation, r; (both variables are continuous and quantitative) Mathematics achievement and mathematics anxiety Phi coefficient is the Pearson correlation for two variables that are both qualitative and dichotomous Gender and Science major or not Spearman s rho (both variables are expressed as ranks) Class rank and ranking in a science fair competition
8 Tests of Significance Simple Analysis of Variance ( one independent variable; gender (IV) and college gpa) MultiFactor Analysis of Variance (two or more independent variables; gender, SES, participation in summer bridge program, college freshman gpa) Multiple Regression (tells us how much of the variance in the dependent variable is explained by the set of independent variables; high school gpa, SAT/ACT mathematics and verbal scores, freshman college gpa.
9 Correlational Techniques Correlation: A measure of the degree of association between two or more variables. Biserial correlation (one variable is continuous and quantitative and the other would be, expect it has been reduced to two categories) Multiple correlation, R, is the Pearson correlation between the variable to be predicted and the bestweighted combination of several predictors. To calculate R, we must know Pearson s r between each pair of variables.
10 Qualitative Research
11 Data Analysis Data analysis in qualitative research involves summarizing data in a dependable and accurate manner that has an air of undeniability. Data interpretation is an attempt by the research to find meaning in the data and answer the question, So What?
12 Data Analysis Engage in a great deal of analysis before data collection is complete. Reflect on two questions Is the research questions still answerable? Are the data collection techniques catching the kind of data that is wanted and filtering out the data that is not wanted. Avoid premature actions based on early analysis and interpretation of data.
13 Data Analysis Qualitative data analysis is a cyclical, iterative process of reviewing data for common topics or themes. One approach is to follow three iterative steps: Reading and memoing Describing what is going on in the setting Classifying research data
14 Data Analysis Strategies Identifying Themes  emerges for ideas found in the review of the literature and the data collection. Coding  the process of marking units of text with codes or labels as a way to indicate patterns and meaning in data. Asking questions Who is centrally involved? ; What major activities or issues are relevant to the problem? ; then seeking answers in the data Concept Mapping a visual display of the major influences that have affected the study.
15 Data Analysis Computer software Many computer programs are available to aid in analyzing qualitative data, but it is important for novice qualitative researchers to remember that computers do not analyze of code data; researchers do. Thus, the data must be prepared before it is subjected to computer analysis.
16 Questions?
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