inferential testing

• What is the purpose of inferential statistical testing?

  To determine significance and hypothesis acceptance
• What does a significant result in inferential statistics indicate?

  Confidence in the result's significance
• What is the null hypothesis?

  No difference or correlation exists
• What are the two types of alternative hypotheses?

  Non-directional and directional
• What are the levels of measurement in statistics?

  • Nominal data: categorical, cannot be ranked
  • Ordinal data: ranked, no fixed intervals
  • Interval data: ranked, fixed intervals, can calculate all measures
• What is nominal data?

  Named or categorical data
• What is the only measure of central tendency for nominal data?

  The mode
• What characterizes ordinal data?

  Can be ranked but lacks fixed intervals
• What measures can be calculated for ordinal data?

  Mode, median, and range
• Why can't you calculate the mean for ordinal data?

  Intervals are not standardized
• What is interval data?

  Ranked data with fixed intervals
• What measures can be calculated for interval data?

  Mode, median, mean, range, and standard deviation
• What is the significance of fixed intervals in interval data?

  Distance between units is consistent
• What steps should you follow to choose the right statistical test?

  1. Identify the study's focus: difference, association, correlation
  2. Determine the level of measurement: nominal, ordinal, interval
  3. Decide on the experimental design: repeated measures, matched pairs, independent groups
• What is the calculated value in statistical testing?

  The end product of the formulas
• What is compared to the calculated value?

  The critical value
• What does each statistical test have?

  A corresponding table of critical values
• What is the sample size referred to in statistical testing?

  N or df for chi-squared
• What is the usual confidence level in statistical testing?

  0.05