Statistics used in quantitative Research.pptx

statistics used in research

1. A SST . P ROF. R EA J OAN M . A TIENZA STATISTICS INSTRUCTOR, FACULTY EXTENSIONIST, PUP SANTA ROSA CAMPUS

2. Research Methodology General Specific Specific Types of Quantitative Research Method 1. Descriptive research seeks to describe the current status of an identified variable. These research are designed to provide systematic information about a phenomenon. The researcher does not usually begin with a hypothesis, but is likely to develop one after collecting data

3. Correlational research attempts to determine the extent of a relationship between two or more variables using statistical data. In this type of design, relationships between and among a number of facts are sought and interpreted. This type of research will recognize trends and patterns in data Causal-comparative research attempts to establish cause-effect relationships among the variables (usually categorical vs numerical data). These types of design are very similar to true experiments, but with some key differences. An independent variable is identified but not manipulated by the experimenter, and effects of the independent variable on the dependent variable are measured.

4. Experimental research , often called true experimentation, uses the scientific method to establish the cause-effect relationship among a group of variables that make up a study. An independent variable is manipulated to determine the effects on the dependent variables.

5. Types of Quantitative Research Designs DESCRIPTIVE CORRELATIONAL CASUAL COMPARATIVE EXPERIMENTAL

6. Let’s try the following: 1. The perception of parents about the possible face to face classes next school year. 2. The relationship between intelligence and self-esteem 3. The effect of gender on algebra achievement 4. A comparison of the effect of personalized instruction vs. traditional instruction on computational skill 5. The effect of teaching with a cooperative group strategy or a traditional lecture approach on students’ achievement

7. Sampling Techniques Probability sampling:  Participants of a sample are chosen using random selection processes. Each member of the target audience has an equal opportunity to be selected in the sample.

8. Simple random sampling:  As the name indicates, simple random sampling is nothing but a random selection of elements for a sample. This sampling technique is implemented where the target population is considerably large.

9. Sample Size using Population Proportion

10. Stratified random sampling:  In the stratified random sampling method, a large population is divided into groups (strata), and members of a sample are chosen randomly from these strata. The various segregated strata should ideally not overlap one another.

11. Cluster sampling usually analyzes a particular population in which the sample consists of more than a few elements, for example, city, family, university, etc. Researchers then select the clusters by dividing the population into various smaller sections.

12. Systematic sampling is an extended implementation of the same old probability technique in which each member of the group is selected at regular periods to form a  sample . There’s an equal opportunity for every member of a population to be selected using this sampling technique.

13. HYPOTHESIS TESTING

14. When Santa was a young man, he had to take a Statistics course. When the class started covering two-tailed hypothesis tests, he had a lot of trouble remembering where to put the equal sign. He started repeating to himself “The equal sign goes in the null hypothesis. The equal sign goes in the null hypothesis. The equal sign goes in the null hypothesis.” Eventually Santa had to shorten this phrase to make it easier to remember. In fact, to this day, you can still hear him say “Ho, Ho, Ho.”

15. Decision Rule Ho: mean 1 = mean 2: THERE IS NO SIGNIFICANT DIFFERENCE/RELATIONSHIP Ha: THERE IS SIGNIFICANT DIFFERENCE/RELATIONSHIP

16. If p computed is less than the level of significance (0.05) REJECT HO Therefore, THERE IS SIGNIFICANT DIFFERENCE/RELATIONSHIP If p computed is greater than the level of significance (0.05) ACCEPT HO/FAIL TO REJECT HO Therefore, THERE IS NO SIGNIFICANT DIFFERENCE/RELATIONSHIP

17. Hypothesis Testing using Parametric Data Parametric tests  assume a normal distribution of values, or a “bell-shaped curve.” Parametric tests are in general more powerful (have greater statistical power) than  nonparametric tests .

18. Research Question Null Hypothesis Statistical Method Purpose of Test Nature of Data/Conditions Is the mean posttest score of Group A higher than its pretest mean score? Mean posttest score of Group A is not significantly higher than its pretest mean score. Paired or related sample t-test, (one-tailed), effect size Compare two mean scores 2 related or paired groups, at least 30 subjects, normal distribution, interval data Is the mean score of Group A different from Group B? There is no significant difference between the mean scores of Groups A and B. Independent or unrelated samples t- test, (two-tailed) 2 unrelated or independent groups, at least 30 subjects per group, normal distribution, interval data D I F F E R E N C E

19. Research Question Null Hypothesis Statistical Method Purpose of Test Nature of Data/Conditions Are mean scores of Groups A,B and C different? Mean scores of Groups A, B, and C do not significantly differ Analysis of Variance (ANOVA). Pairwise comparisons for significant F-ratio Compare 3 or more mean scores 3 or more related or unrelated groups; nominal data – 1 or more independent or classification variables; interval data – one dependent variable D I F F E R E N C E

20. Research Question Null Hypothesis Statistical Method Purpose of Test Nature of Data/Conditions Does independent variable X predict, influence, or affect dependent variable Y Is there significant Relationship between x and y? Variable X is not a significant predictor of Y. There is no significant Relationship between x and y. Linear Regression (Significance of beta or regression coefficient; proportion of variance in Y explained by X). Y = a + bX Pearson r Determine influence of X on Y and proportion of variation Y explained by X; Determine if linear relationship exists X and Y have theoretical cause-effect relationship; interval data - X and Y. Minimum of 7 pairs of data/Applicable for numerical data R E L A T I O N S H I P

21. Research Question Null Hypothesis Statistical Method Purpose of Test Nature of Data/Conditions What is the relative contribution of Xs to Y? Taken together, the Xs do not significantly predict Y. Multiple regression: Y = a + (b1) (X1) + (b2) (X2) +…+(bn)(Xn) Determine relative influence of Xs on Y and proportion of variation in Y explained by Xs. Interval data - Xs and Y; sample size is at least ten times the number of Xs; Xs and Y have theoretical causal relationships. R E L A T I O N S H I P

22. Research Question Null Hypothesis Statistical Method Purpose of Test Nature of Data/Conditions Does variable x has something to do with Y? Is there significant Relationship between x and y? Is there a connection between variable x and Y? Y is independent of x. There is no significant relationship between the two Chi square test of Independence Determine if there is an association between x and y Minimum of 5 in each input, used for categorical data R E L A T I O N S H I P

23. REFERENCES https://www.wssu.edu/about/offices-and-departments/office-of-sponsored-programs/pre-award/_Files/documents/develop-quantitative.pdf https://www.questionpro.com/blog/probability-sampling/ Talisayon, V., 2020, Statistical Methods in Educational Research https://www.pinterest.ph/pin/533887730809876046/ https://www.analyticsvidhya.com/blog/2021/06/hypothesis-testing-parametric-and-non-parametric-tests-in-statistics/ https://simplyeducate.me/2020/09/19/parametric-tests/ https://goodcalculators.com/sample-size-calculator/

24. Homework: A. Identify the type of research method to be used in the following cases: 1. Tally of the demographic profile of all the employees in a company 2. Study of whether educational background has influence over the product acceptability of the respondents 3. Finding if relationship exists between performance evaluation and intrinsic motivation among the consumers 4. Determining if product A tastes better than product B B. Answer the following questions, show necessary solutions. How many sample respondents are needed if population proportion is 40% and confidence level is 95%. If p value computed is 0.04, then the null hypothesis should be rejected. T or F. If p value computed is greater than the level of significance, then there is no enough basis to reject the null hypothesis. T or F Suppose you choose employees of company B as your respondents, what sampling technique should you utilize? Defend your answer. C. Create a sample research title, then decide the research method, sampling technique, sample size and possible null hypothesis. Justify each choice.

25. LET’S GO TO EXCEL!