LESSON 13 of Practical Research Grade 12.pptx

This is lesson 13 for PR

1. LESSON 13 QUANTITATIVE DATA ANALYSIS

2. To understand the numbers standing for the information, you need to analyze them, that is, you have to examine or study them not by taking the data as a whole, but by separating it into its components.

3. Examine each part or element to see the relationships between or among the parts to discover the orderly or sequential existence of these parts, to search for meaningful patterns of the components, and to know the reasons behind the formation of such variable patterns.

4. Steps in Quantitative Data Analysis

5. STEP 1: PREPARING THE DATA Keep in mind that no data organization means no sound data analysis. Hence, prepare the data for analysis by doing these two preparatory sub steps first:

6. Coding System Converting the words, images, or pictures into numbers, they become fit for any analytical procedures requiring knowledge of arithmetic and mathematical computations Assigning numerical values to categorical or qualitative responses to make them analyzable. For example: "Male" = 1, "Female" = 2 "Strongly Agree" = 5, ..., "Strongly Disagree" = 1

7. Data Tabulation For easy classification and distribution of numbers based on a certain criterion, you have to collate them with the help of a graph called table. Organizing raw data into tables or spreadsheets for easy viewing and analysis.

8. SATISFACTORY LEVEL FREQUENCY VERY SATISFIED 12 SATISFIED 18 NEUTRAL 5 DISSATISFIED 3 VERY DISSATISFIED 2

9. STEP 2: ANALYZING THE DATA Data coding and tabulation are the two important things you have to do in preparing the data for analysis. Before immersing yourself into studying every component of the data, decide on the kind of quantitative analysis you have to use, whether to use simple descriptive statistical techniques or advanced analytical methods. Summarizing and describing features of the data.

10. 1. Descriptive Statistical Technique This quantitative data analysis technique provides a summary of the orderly or sequential data obtained from the sample through the data gathering instrument used. Summarizing and describing features of the data. (Frequency Distribution , Measure of Central Tendency, Standard Deviation )

11. Frequency Distribution Gives you the frequency of distribution and percentage of the occurrence of an item in a set of data. In other words, it gives you the number of responses given repeatedly for one question.

12. Question: By and large, do you find the senators’ attendance in 2015 legislative sessions awful? Measurement Scale Code Frequency Distribution Percent Distribution Strongly Agree 1 14 58 % Agree 2 3 12 % Neutral 3 2 8 % Disagree 4 1 4 % Strongly Disagree 5 4 17 %

13. Measure of Central Tendency Mean = average of all the items or scores Example: 3 + 8+ 9+ 2+ 3+ 10+ 3= 38 | 38 ÷ 7= 5.43 (Mean) Median - the score in the middle of the set of items that cuts or divides the set into two groups Example: The numbers in the example for the mean has 2 as the median. Mode - refers to the item or score in the data set that has the most repeated appearance in the set Example: Again, in the given example above for the mean, 3 is the mode.

14. Standard Deviation Shows the extent of the difference of the data from the mean. An examination of this gap between the mean and the data gives you an idea about the extent of the similarities and differences between the respondents. There are mathematical operations that you have to do to determine the standard deviation. These are as follows:

15. s = sample standard deviation x i = each individual value in the dataset x̄ = sample mean (average of all values) n = number of values in the sample ∑ = sum of all the terms

16. Step 1 . Compute the mean. Step 2 . Compute the deviation (difference) between each respondent's answer (data item) and the mean. The plus sign (+) appears before the number if the difference is higher; the negative sign (-) appears if the difference is lower. Step 3 . Compute the square of each deviation. Step 4 . Compute the sum of squares by adding the squared figures . Step 5 . Divide the sum of squares by the number of data items to get variance. Step 6 . Compute the square root of variance figure to get the standard deviation.

17. 2. Advanced Quantitative Analytical Methods These techniques go beyond description and are used to test hypotheses or explore complex relationships Correlation and Regression Analysis - for comparing groups T-test, Analysis of variance (ANOVA) - to measure relationships Chi-square Test - for categorical data comparisons Factor Analysis, MANOVA - for more complex multivariate analysis