Chapter+Six+-+Data+Analysis

=Chapter Six: Data Analysis =



The purpose of this chapter is to offer an overview of various qualitative and quantitivate methods of data analysis. It is not meant to provide an exhaustive list or discussion of data analysis or statistics; however, it will describe the rationales and common approaches which are appropriate for classroom research.

=I. Overview of Data Analysis= Data analysis is the process of applying techniques statistically or logically in order to evaluate the data collected. There are specific approaches to analyzing the data. The approaches used must be determined according to the type of research performed. Generally, qualititative data analysis uses content or constant comparative methods among others while quantitative data analysis uses descriptive or inferential methods.

I.2. Quantitative Data Analysis
=II. Specific Qualitative Approaches to Data Analysis=

Content Analysis is when you are looking for specific information based on the content. If a researcher is teaching writing from a specific textbook they may want to examine how the textbook might have changed over time. A researcher may also evaluate if the content of the writing procedure taught was implemented in the students' writing compositions.

II.3. Other methods
=III. Specific Quantitative Approcahes to Data Analysis=

III.2. Inferential Statistics
Inferential statistics is the process of comparing means between two or more groups. Inferential statistics is a method used to represent quantitative data analysis. Inferential statistics can be used to compare one sample, independent samples, or paired samples. In a one sample comparison the t-test compares a group with a “normed” mean. The Stanford test compares groups by grade level based on a “normed” mean. An independent sample t-test compares two independent groups. A school or school district may choose to use the TAKS test results to compare the bilingual students with the English students. In a paired sample t-test, the same individuals are compared on two different measures. This type of comparison is made my using a pre-test/post-test method. The students take a test at the beginning of the year to determine the prior knowledge of the students. This same test or a different test with the same objectives can be administered at the end of the year to determine student growth. The results of the test are compared and measured against one another. Inferential statistics can also be used to compare three or more means. When comparing three or more means an ANOVA is used. An ANOVA is an analysis of variances.

III.3. Advanced Modeling Methods
=IV. Summary= There are many ways and methods to analyze data. When a researcher plans their study they must determine what kind of data they are going to collect and how they plan on analyzing it. Many people would assume that data analysis requires lots of statistics and computations but it goes beyond that. Data analysis can be broken down into different kinds of charts and models depending on the type of data that needs to be collected. These models and test allow the researcher to compare the numbers directly. The whole point of the study is to let the numbers do the talking. The numbers will prove the point and thus it is essential that that data is analyzed correctly and efficiently.