Week 11: Statistical Evaluation of Data

• Descriptive Statistics


  Methods that help researchers organise, summarise, and simplify the results obtained from research studies. The two techniques of this are tables/graphs and numerical measures.
• Frequency Distribution


  Indicate the number of participants who receive or select each possible score on a variable. This shows the categories of the score and the frequency of the scores.
• What are the several graphs that are used to depict frequency tables?

  1. Pie Chart
  2. Bar Graphs
  3. Histograms
  4. Polygons
• Mean


  The mathematical average–individual scores are added and then divided by the number of scores. Outlier scores skew this measurement towards the said score. This is used for interval and ratio scales.
• Median


  The score that divides the distribution in half. This is used for ordinal, interval, and ratio scales. We can use the median to be more representative in comparison to the mean.
• Mode


  The score or category with the greatest frequency. This is used for all scales.
• Standard Deviation


  Average deviation of scores from the mean. Used for itnerval and ratio scales.
• What does a small standard deviation mean?

  It means it is closer to the mean and there is less variability around the scores.
• What does a larger standard deviation mean?

  A larger standard deviation means that there is large variability around the scores.
• Inferential Statistics


  Methods that use the results obtained from samples to help make generalisations about populations.
• What does inferential statistics allow us to do?

  Allows us to judge whether the difference between means reflects a real difference or if it is due to error.
• What are the four steps to hypothesis testing?

  1. Specify hypothesis.
  2. Collect data.
  3. Calculate whether the difference in scores between groups is significant or not.
  4. If it is significant, then we can conclude that our difference is true and not due to error.
• What is the goal of hypothesis testing?

  The goal of hypothesis testing is to reject the null hypothesis. By doing this, it shows that we have support for the research hypothesis.
• What are the two factors that influence significance tests?

  1. Sample Size: This means a difference found with a large sample and is more likely to be significant than the same result with a small sample.
  2. Variability of Scores: A sample mean with high variance and is less likely to be significant than the same result found with low variance.