Data Analysis (Qualitative & Quantitative)

Data Analysis is a process of understanding the collected data using statistical treatment (quantitative) or thematic analysis (qualitative) to come-up with meaningful conclusion that satisfies your objectives of study. While according to Baraceros (2015), “its a process of understanding data or known facts or assumptions serving as the basis of any claims or conclusions you have about something.”

How to write  Data Analysis

• What is your objective?

• What is your treatment or method in understanding the data? (statistical tool or thematic analysis) why?

• How will you get the conclusion from   your treatment or method?

Statistical tool (Quantitative)

•  Correlation describes the relationship of 2 variables and also tests the strength or significance of their linear relation.

-  Spearman's rho- measures the dependency of dependent to independent variable

-  Chi-  squre  - test whether or not relationship exist between among variables, and tests whether caused by chance

-  T test- the mean of the sample reflects the mean of the population where the sample was drawn.  It also tests the difference of between two means.

•  Regression- determine how strong relationship of the variables are.

Thematic Analysis

Methods of Collection of Data

• Observation

• Interview

• Questionnaire

Data Analysis

Coding- using symbols like letters or words to represent data.

Collating- bringing together the coded data

Sample Thematic Analysis

  The first objective was analyzed by getting the mean difference of post-test and pretest results of each strategy. Then, divide the mean difference of posttest and pretest with the result of the mean posttest. The results were the academic performance in terms of teaching strategy applied. These were being compared to each of the strategies. The higher the value of academic performance being compared to others, the better the strategy that was applied respectively.

   The second objective was measured by getting the differences of posttest and pretest of each strategy and use ANOVA with the SPSS tool to come up with significant difference among strategies. The SPSS software is built with Least Square Method Multiple Comparisons to compare the significant differences of strategies with one another. The value of alpha was 0.10. If the value of ANOVA is greater of 0.10, this suggests that there is no significant difference among the strategies. But if the value is 0.10 and below the critical value, this would suggest that there is significant difference among the strategies. The Least Square Method further breaks down the significant differences into pairs among the strategies being applied.

   The third objective was analyzed through thematic analysis based from the responses of the interviewees. The results of the interview were backed-up with feed backing among the teachers of the students. While the fourth objective was come-up with the collaboration among the teachers of the school with respect to the responses of the interview.

Video below  explained in Filipino the Data Analysis

To download the Powerpoint presentation used, click the link below

Data Analysis (ppt)