Now you have collected your data you need to prove the results. Inferential statistics help you do this. Inferential statistics assess relationships or differences between data sets. For example if you wanted to find out whether PNF stretching increases hamstring flexibility, you would use an appropriate inferential test to get your answer.
Inferential tests can be subdivided into either Parametric or NonParametric
Parametric tests use
interval or ratio data and only use data that has normal distribution
There are 3 different Parametric tests you can choose from:

Option 1 Dependent TTest

Option 2 Independent TTest

Option 3 Pearson Product Moment Correlation Coefficient
NonParametric tests use
ordinal or nominal data
There are 3 different NonParametric tests you can choose from:

Option 1  Wilcoxon MatchedPairs SignedRanks Test

Option 2  MannWhitney U Test

Option 3  Spearman's Rank Order Correlation Coefficient
Option 1 dependent TTest
You use a dependent TTest when you want to prove or disprove there is a difference between two related scores. By related scores it could mean comparing the same subjects' scores before and after an intervention. For example, is there a significant difference between subjects' number of shots on target before and after a practice drill?
After watching video: Your Excel is slightly different. Instead of going to "Tools" and then "Data Analysis", go to "Data" then "Data Analysis"
Option 2Independent TTest
You use an independent TTest when you want to prove or disprove there is a difference between two different group's scores. For example males compared to females, Man Utd compared to Fulham FC, Creatine compare to protein. For example, is there a significant difference between the group taking creatine and the group taking protein?
After watching video: Your Excel is slightly different. Instead of going to "Tools" and then "Data Analysis", go to "Data" then "Data Analysis"
Option 3 Pearson ProductMoment Correlation Test
Used if you are trying to identify a relationship (correlation) between two variables. For example is there a correlation between number of calories eaten and amount of body fat? Is there a relationship between taking protein shakes and an increase in muscle mass? Is there a relationship/correlation between the number of shots taken by a player and their confidence levels?
After watching video: Your Excel is slightly different. Instead of going to "Tools" and then "Data Analysis", go to "Data" then "Data Analysis"
Option 1 Wilcoxon MatchedPairs
SignedRank Test
The Wilcoxon matchedpairs signedrank test is the nonparametric equivalent to the dependent ttest. Therefore, you would use if you are trying to see a difference between 2 scores from the same group and you are using nominal and ordinal data.
Option 2 Mann Whitney U Test
Mann Whitney U Test is the nonparametric equivalent to the independent ttest. Therefore, you would use if you are trying to see a difference between 2 different groups and you are using nominal and ordinal data.
Option 3  Spearman's Rank
Order Correlation Test
Spearman's rank order correlation test is the nonparametric equivalent to the Pearson productmoment correlation coefficient test. Therefore, you would use if you are trying to see a relationship/ correlation between 2 variables and you are using nominal and ordinal data.