Research Methods and Statistics
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Questions and Answers

What is the term for failing to reject the null hypothesis when it is false?

  • Beta (β) (correct)
  • Type II error
  • Alpha (α)
  • Type I error

    • What happens when alpha is greater than 0.05?

  • We are less prone to type I errors
  • We are more prone to type I errors (correct)
  • We are certain of the correct outcome
  • We are more prone to type II errors

    • What is the consequence of setting alpha at 0.01?

  • We are more prone to type II errors (correct)
  • We are less prone to both type I and type II errors
  • We are certain of the correct outcome
  • We are more prone to type I errors

    • What is the term for rejecting the null hypothesis when it is true in the underlying population?

    <p>Type I error</p> Signup and view all the answers

    What is the effect of decreasing alpha?

    <p>We are more prone to type II errors</p> Signup and view all the answers

    What is the relationship between alpha and type I errors?

    <p>As alpha increases, type I errors increase</p> Signup and view all the answers

    What is the consequence of setting alpha at 0.10?

    <p>We are more prone to type I errors</p> Signup and view all the answers

    What is the term for the probability of rejecting the null hypothesis when it is true?

    <p>Alpha (α)</p> Signup and view all the answers

    What is the effect of increasing alpha?

    <p>We are more prone to type I errors</p> Signup and view all the answers

    What is the consequence of setting alpha at 0.01?

    <p>We are less prone to type I errors</p> Signup and view all the answers

    Study Notes

    Research Methods

    • There are two main methods of research: deduction and induction
      • Deduction: general theory to particular data
      • Induction: particular data to a general theory

    Measurement Scales

    • There are four types of measurement scales:
      • Nominal: categorical data with no order or equal intervals
      • Ordinal: categorical data with order, but no equal intervals
      • Interval: distances between each interval on the scale are equal
      • Ratio: equal intervals with a true zero point

    Theory and Hypothesis

    • Theory: an explanation or set of principles that is well substantiated by repeated testing and explains a broad phenomenon
    • Hypothesis: a specific prediction made by a theory

    Analyzing Data

    • Descriptive statistics: methods for summarizing and describing data
    • Frequency distribution/histogram: a graph plotting values of observations on the horizontal axis, with a bar showing how many times each value occurred in the data set
    • Stem and leaf plots: similar to histograms, but the frequency of occurrence of a particular score is represented by repeatedly writing the particular score itself
    • Box and whisker plots: enable us to easily identify extreme scores and see how the scores in a sample are distributed
    • Scattergram: gives a graphical representation of the relationship between two variables

    Normal Distribution

    • A symmetric distribution where most of the observations cluster around the central peak
    • Can be used to analyze data by transforming scores to standard normal scores

    Dispersion

    • The extent to which a distribution is stretched or squeezed
    • Quartiles: three values that split the sorted data into four equal parts
      • Lower quartile: median of the lower half of the data
      • Upper quartile: median of the upper half of the data
      • Interquartile: difference between the upper and lower quartile

    Confidence Intervals

    • Point estimate: a single figure estimate of an unknown number
    • Interval estimate: a range within which we think the unknown number will fall
    • Standard error: the deviation of a sample mean from the actual mean of a population

    Errors in Hypothesis Testing

    • Type I error: rejecting the null hypothesis when it is true
    • Type II error: failing to reject the null hypothesis when it is false
    • Alpha (α): the probability of a type I error
    • Beta (β): the probability of a type II error
    • The larger the sample size, the lower the sampling error

    One-Tailed and Two-Tailed Tests

    • One-tailed test: tests a directional hypothesis (e.g. "there is a significant increase in...")
    • Two-tailed test: tests a non-directional hypothesis (e.g. "there is a significant difference in...")

    Setting Alpha at 0.05

    • If alpha > 0.05, then we are more prone to type I errors
    • If alpha < 0.05, then we are more prone to type II errors

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    Description

    This quiz covers two main methods of research, including deduction and induction, and statistical concepts like interval scales. It also includes ranking students based on their grades.

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