Statistical Tests

• Measure of Central Tendency


  This is a single value that represents the center point of a dataset. This value can also be referred to as “the central location” of a dataset.
• Mean


  Average Score, Not skewed
• Median


  Middle Score, Highly skewed
• Mode


  Most frequent score
• Range


  The difference between maximum and minimum scores.
• Standard Deviation


  The average distance of observations.
• Variance


  The average squared differences.
• Bar Graphs


  This graph is used to compare groups.
• Line Graphs


  This graph is used to show changes over time.
• Pie Graph


  This graph is used to depict parts of a whole.
• Process of Analyzing Quantitative Data:

  1. Prepare and organize the data for analysis
  2. Data Analysis
  3. Report the results
  4. Interpret the results from the data analysis.
• Level of Measurement:

  1. Nominal
  2. Ordinal
  3. Interval
  4. Ratio
• Nominal Measurement


  It deals with non-numeric variables or where the numbers have no value. It only categorizes the characteristics or identity of the variable and their order does not matter.
• Ordinal Measurement


  It also categorizes the characteristics or identity of the variable but the order or rank of each category matters.
• Interval Measurement


  The order matters and that there is an equal distance between each.
• Ratio Measurement


  The highest level of measurement. There is an equal distance between each interval and the order matters. On top of that, ratio between two sets of data is meaningful.
• One Sample


  You are comparing their statistic against a hypothesized value, a historic value, or a global value.
• Two Samples or More


  This is when you have two or more samples in your study that are independent from each other, and you are comparing their sample statistics.
• Paired Samples


  This is when you have two different samples but are naturally paired or when you measured two different variables from one sample.
• Purpose of Analysis:

  A) 1-sample Proportion Test

  B) 2-sample Proportion Test

  C) Chi-square Test

  D) 1 sample t-test

  E) 2 sample t-test

  F) Correlation / Regression