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# Chosing the appropriate_statistical_test

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### Chosing the appropriate_statistical_test

1. 1. • Univariate • Bivariate • Multivariate
2. 2.  Descriptive Statistics  Inferential Statistics
3. 3.  Descriptive analysis refers to transformation of raw data into a form that will facilitate easy understanding and interpretation. The ways of summarizing data are by calculating average, range, standard deviation, frequency etc.
4. 4.  Inferential statistics is concerned with making predictions or inferences about a population from observations and analyses of a sample. That is, we can take the results of an analysis using a sample and can generalize it to the larger population that the sample represents. Examples of inferential statistics include t-test, regression analysis, correlation analysis, ANOVA.
5. 5.  the t-test compares the actual difference between two means in relation to the variation in the data.  Usually have two groups  Pre-test and post–Test analysis  dependent and independent variable  Multiple test apply
6. 6.  Correlation measures the degree of association between two or more variables. There are three types of correlation:-  Positive Correlation  Negative Correlation  Zero Correlation
7. 7.  ASSOCIATED WITH CORRELATION  HELP IN PREDICTING VALUES OF SINGLE OR SET INDEPENDENT VARIABLE OR NUMERIC DEPENDENT VARIABLE TO GET CERTAIN OUTCOME
8. 8.  Used to two and more than two groups  Compare mean scores  Comparison between different groups Exp: suppose there is three groups- the differences between 1 &2, 2 & 3, 3 &1
9. 9.  One- way, two way, three way ANOVA  Analysis of impact of one or more independent variable (exp: BP is higher of male)  Two types of factorial ANOVA BETWEEN GROUPS DIFFERENT GROUPS REPEATED NUMBERS OF AVOVA
10. 10. IDENTIFY AND DEFINE YOUR VARIABLE Cause and effect relationship Dependent (blood pressure and muscles pain) and independent variables (comparison between male / female) (comparision between public sector bank and private sector banks) (comparision between football players and basket ball players) OPERATIONAL DEFINITION OF EACH VARIABLE (exp: health measure 1.independent variables may be HAPPY OR UNHAPPY)
11. 11.  IDENTIFY THE NATURE OF VARIABLE i. Level of measurement of each variable ii. Develop measurement scale • Normal / categorical • Ordinal- ranking on five point scale • Interval (exp: temperature, air, water temp) • Ratios (no. of books you read out in library, number of article you read, liquidity ratio, profit earning ratio, assets turnover ratio)
12. 12.  DRAW A DIAGRAM • Summarize key points in a diagram • Identify type of questions, Variables (exp; is there a relationship between blood pressure and body weight) scatter diagram (exp: do peoples BMI values below 25 have lower BP than people having BMI above 25) BMI GREATER 25 BMI LESS THAN 25 MEAN BP
13. 13. Exp: is the effect of sex on BP different for people with BMI values below 25 than people with BMI above 25. Sex – independent category – ale / female BMI – independent category BP- dependent – mean range from 100- 220 S.NO PARTICULARS BMI LESS 25 BMI GREATER 25 1 MEAN BP MALE 2 MEAN BP FEMALE
14. 14.  DETERMINE NEED FOR PARAMATRIC AND NON-PARAMETRIC TEST • DOES YOUR DATA MEET THE ASSUMPTION OF PARAMATRIC TESTING (exp: t’ test, ANOVA) • What if it does’t?  use parametric testing any way  Possible in larger sample size  Violate some assumption/ justify  Data transform
15. 15.  Make a final decision • Make determination about your variables • Make sure you meet all the assumptions • Are there other approaches that could be taken • What approaches have used by other studies with similar design • Exp: RQ- what is the relationship between gender and having a diagnosis of clinical dieses
16. 16.  One independent variable i.e; male/ female  One category dependent variable i.e: diagnosis of depression yes/ no Test of independence – chi- square patients male female Have depression Does not have depression
17. 17.  Exp: RQ: is there a relationship between age and depression index? Does depression needed with age. Pearson's correlation  exp: male more depressed than female • Dependent variable- male • Independent variable- female Parametric- Independent t’ test
18. 18.  Exp: will 10 week of exercise have reduced the BP  Independent variables: pre- test and post- test  Dependent variable: BP  Parametric test- t’ test  Non- parametric test- rank test
19. 19. Exp 6: what is the effect of age on BP score for male/ female  Two continuous independent variable (gender: male/ female, age ≤ 30, 31-49, 50 & above)  Dependent variable: BP  Parametric test: two ways ANOVA  Non parametric test: none
20. 20. Exp: do male have over all rating of psychological health (depression, anxiety, perceived stress) than female  Independent variable (male/ female)  Dependent variable (psychological health)  Parametric test- MANOVA  Non-parametrictest- none male female Mean anxiety score Mean depression Mean preceived stress
21. 21. THANK YOU
• #### AngelicaPerez134

Nov. 19, 2018
• #### harry665

Sep. 22, 2017

Aug. 5, 2017
• #### OhnmarMyo1

Sep. 21, 2016
• #### SumitSen11

Aug. 11, 2016

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