Statistics in Research

Def: Statistics is the science of collecting, organizing, analyzing, and interpreting data in order to make decisions.

Why we use Statistics?

• To mathematically describe/depict our findings
•  To draw conclusions from our results
• To test hypotheses
• To test for relationships among variable
• Numerical representations of our data.

Types of Statistics:

1. Descriptive statistics
2. Inferential statistics

1. Descriptive statistics:

                             it summarize data

       2.Inferential statistics

are tools that indicate how much confidence we can have when we generalize from a sample to a population.

Why we use statistics?

1. Be sure our data is valid and reliable
2. Be sure we have the right type of data
3. Be sure statistical tests are applied appropriately
4.  Be sure the results are interpreted correctly
5.  numbers may not lie, but people can

Levels of Measurement 

the relationship among the values that are assigned to a variable and the attributes of that variable.

1. Nominal- naming e.g (cat,dog,lion)
2. Ordinal- rank order
3. Interval- equal intervals between values
4.  Ratio- equal intervals AND an absolute zero (i.e. a ruler)

Statistics types:

´  Descriptive Statistics

´   Inferential Statistics

Descriptive Statistics:

1.          Number
2.       Frequency Count
3.          Percentage
4.           Deciles and quartiles
5.       Measures of Central Tendency (Mean, Midpoint, Mode)
6.       Variability
7.       Variance and standard deviation
8.       Graphs
9.       Normal Curve

Inferential Statistics:

Correlation—the extent to which two variables are related across a group of subjects.

Pearson r:

•  It  can range from -1.00 to 1.00.
•  -1.00 is a perfect inverse relationship—the strongest possible inverse relationship
• 0.00 indicates the complete absence of a relationship
• 1.00 is a perfect positive relationship—the strongest possible direct relationship
• The closer a value is to 0.00, the weaker the relationship
• The closer a value is to -1.00 or +1.00, the stronger it is 

More tests:

1. Spearman rho
2. t-test
3. Analysis of variance
4. Regression analysis