Statistical Methods in Psychology
64 Questions
8 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

Which reliability method uses the Kappa Statistic for statistical treatment?

  • Alternate-Forms Immediate
  • Test-retest
  • Internal Consistency - Cronbach's Alpha
  • Inter-rater (correct)

    • How many forms are used in the Test-retest reliability method?

  • 4
  • 1 (correct)
  • 3
  • 2

    • What source of error is associated with the Internal Consistency - Split-Half method?

  • Sample Selection
  • Scoring and interpretation
  • Test Administration
  • Test Construction (correct)

    • Which reliability method uses both Pearson-R and Spearman-Brown for statistical treatment?

    <p>Internal Consistency - Split-Half</p> Signup and view all the answers

    What is the statistical treatment for the Alternate-Forms Immediate reliability method?

    <p>Pearson-R</p> Signup and view all the answers

    Which reliability method involves two forms and two sessions?

    <p>Alternate-Forms Delayed</p> Signup and view all the answers

    Which reliability method has scoring and interpretation as its source of error?

    <p>Inter-rater</p> Signup and view all the answers

    What statistical treatment is used for Internal Consistency?

    <p>Cronbach's Alpha or KR-20</p> Signup and view all the answers

    What is the source of error for the Test-retest method?

    <p>Test Administration</p> Signup and view all the answers

    Which reliability method involves only one form and one session?

    <p>Internal Consistency - Split-Half</p> Signup and view all the answers

    Which reliability method uses Pearson-R for statistical treatment and involves only one form and one session?

    <p>Internal Consistency - Split-Half</p> Signup and view all the answers

    Which type of error is associated with the Inter-rater reliability method?

    <p>Scoring and interpretation</p> Signup and view all the answers

    What statistical treatment is used for the Test-retest reliability method?

    <p>Pearson-R</p> Signup and view all the answers

    Which reliability method involves two forms and one session?

    <p>Alternate-Forms Immediate</p> Signup and view all the answers

    Which test compares the medians of 2 independent samples?

    <p>Median Test</p> Signup and view all the answers

    Which test is used to compare two correlated samples by obtaining the differences between each pair of observations?

    <p>Fisher's Sign Test</p> Signup and view all the answers

    Which test uses rank data to compare 2 independent samples?

    <p>Wilcoxon Rank Sum Test</p> Signup and view all the answers

    Which test is used with independently drawn random samples where the sizes of the samples need not be the same?

    <p>Mann-Whitney (U) Test</p> Signup and view all the answers

    Which test is used to determine if a group of independent samples is from the same or different populations?

    <p>Kruskal-Wallis H Test</p> Signup and view all the answers

    Which test is used for correlated samples where the difference between each pair is calculated?

    <p>Wilcoxon Signed-Ranks Test (T)</p> Signup and view all the answers

    Which test is used to test whether data is from the same sample under three different conditions?

    <p>Friedman Rank</p> Signup and view all the answers

    Which test compares the medians of 2 independent samples?

    <p>Median Test</p> Signup and view all the answers

    Which test is used to compare two correlated samples by obtaining the differences between each pair of observations?

    <p>Fisher's Sign Test</p> Signup and view all the answers

    What level of data is used in the non-parametric tests listed?

    <p>Ordinal</p> Signup and view all the answers

    Which test is used with independently drawn random samples where the sizes of the samples need not be the same?

    <p>Mann-Whitney (U) Test</p> Signup and view all the answers

    Which test is used to determine if a group of independent samples is from the same or different populations?

    <p>Kruskal-Wallis H Test</p> Signup and view all the answers

    Which test is used for correlated samples where the difference between each pair is calculated?

    <p>Wilcoxon Signed-Ranks Test</p> Signup and view all the answers

    Which test uses rank data to compare 2 independent samples?

    <p>Wilcoxon Rank Sum Test</p> Signup and view all the answers

    Which test is used to test whether data is from the same sample under three different conditions?

    <p>Friedman Rank</p> Signup and view all the answers

    What can be considered a variable?

    <p>Anything that can change or vary</p> Signup and view all the answers

    What does a correlation measure?

    <p>The relationship between two or more variables</p> Signup and view all the answers

    Which of the following statements is true about correlation?

    <p>Correlation is a statistical measure of the relationship between two or more variables</p> Signup and view all the answers

    Which scenario illustrates a strong correlation?

    <p>A consistent increase in one variable as another increases</p> Signup and view all the answers

    In a study, if two variables are found to have no correlation, what does this imply?

    <p>The two variables have no relationship with each other</p> Signup and view all the answers

    What does the correlation coefficient (r) represent?

    <p>The strength and direction of a relationship between two variables</p> Signup and view all the answers

    What can be derived from the formula for measuring a correlation?

    <p>A number representing the correlation coefficient (r)</p> Signup and view all the answers

    What aspect does not affect the value of the correlation coefficient?

    <p>The scale of the data</p> Signup and view all the answers

    A correlation coefficient (r) value close to zero implies what about the relationship between variables?

    <p>No relationship or a very weak relationship</p> Signup and view all the answers

    Which is a correct interpretation of a correlation coefficient (r) value of -0.85?

    <p>A strong negative relationship between variables</p> Signup and view all the answers

    What does a positive correlation between two variables indicate?

    <p>As one variable goes up, the other goes up as well</p> Signup and view all the answers

    Which of the following is an example of negative correlation?

    <p>Cigarette smoking and life expectancy</p> Signup and view all the answers

    If an increase in perfectionism is related to increased test anxiety, what type of correlation exists between these two variables?

    <p>Positive correlation</p> Signup and view all the answers

    Which statement best describes a negative correlation?

    <p>One variable decreases as the other increases</p> Signup and view all the answers

    Which scenario does NOT illustrate a negative correlation?

    <p>Higher education and higher employment rates</p> Signup and view all the answers

    What correlation coefficient represents the strongest relationship?

    <p>-0.95</p> Signup and view all the answers

    Which correlation value indicates an equally strong relationship as +0.92?

    <p>-0.92</p> Signup and view all the answers

    Which of the following pairs of correlation coefficients represents the strongest relationship?

    <p>+0.45 and -0.90</p> Signup and view all the answers

    If variable A and variable B have a correlation of +0.89, what can be said about their relationship?

    <p>There is a strong positive relationship between the variables.</p> Signup and view all the answers

    Which of the following correctly ranks the strength of correlations from weakest to strongest?

    <p>+0.40, -0.55, -0.75</p> Signup and view all the answers

    The mean is the most appropriate measure of central tendency for nominal data when the distribution is normal.

    <p>False</p> Signup and view all the answers

    The median is used when the distribution is skewed.

    <p>True</p> Signup and view all the answers

    The mode is the most frequently occurring score in a distribution.

    <p>True</p> Signup and view all the answers

    The mean is not influenced by extreme values.

    <p>False</p> Signup and view all the answers

    The median is the 'point of balance' of the distribution.

    <p>False</p> Signup and view all the answers

    What does the standard deviation represent?

    <p>The square root of the variance</p> Signup and view all the answers

    If the standard deviation of a dataset is 8, what is the variance?

    <p>64</p> Signup and view all the answers

    Which of the following is true about variance?

    <p>It is always a positive value</p> Signup and view all the answers

    If the variance of a dataset is 25, what is the standard deviation?

    <p>5</p> Signup and view all the answers

    What additional insight does the standard deviation provide compared to the mean?

    <p>How much the scores deviate from the mean</p> Signup and view all the answers

    If the IQ of a group has an average of 100 and a standard deviation of 15, what is the IQ score that is two standard deviations below the mean?

    <p>70</p> Signup and view all the answers

    What is the implication if an individual's IQ is 115 in the context of its standard deviation?

    <p>One standard deviation above the mean</p> Signup and view all the answers

    Given an average IQ of 100 and SD of 15, what is the range that encompasses approximately 68% of the data?

    <p>85 to 115</p> Signup and view all the answers

    If an IQ test has a mean of 100 and a standard deviation of 15, what is the likely IQ score for someone who is two standard deviations above the mean?

    <p>130</p> Signup and view all the answers

    What percentage of the population falls within one standard deviation of the average IQ score, assuming the SD is 15?

    <p>68%</p> Signup and view all the answers

    Study Notes

    Reliability Methods

    • Test-retest reliability involves administering the same test to the same group of people on two separate occasions.
    • This method has one form and two testing sessions, with statistical treatment using Pearson-R correlation coefficient to calculate the reliability coefficient.
    • Error in test-retest reliability can occur due to test administration.

    Alternate-Forms Reliability

    • Alternate-forms reliability has two forms of a test, which helps to eliminate the issue of memorization.
    • Immediate alternate-forms reliability involves administering both forms to the same group of people at the same time.
    • This method has two forms and one testing session, with statistical treatment using Pearson-R correlation coefficient.
    • Error in immediate alternate-forms reliability can occur due to test construction or administration.

    Delayed Alternate-Forms Reliability

    • Delayed alternate-forms reliability involves administering the two forms with a time interval between them.
    • This method has two forms and two testing sessions, with statistical treatment using Pearson-R correlation coefficient.
    • Error in delayed alternate-forms reliability can occur due to test construction or administration.

    Internal Consistency Reliability

    • Internal consistency reliability can be measured using the split-half method or Cronbach's Alpha/KR-20 method.
    • The split-half method involves dividing the test into two halves and calculating the correlation between them using Pearson-R correlation coefficient and Spearman-Brown prophecy formula.
    • The Cronbach's Alpha/KR-20 method calculates the average correlation between all possible splits of the test.
    • Error in internal consistency reliability can occur due to test construction.

    Inter-rater Reliability

    • Inter-rater reliability measures the consistency of ratings or scores given by different raters.
    • This method involves administering the same test to the same group of people, with statistical treatment using the Kappa statistic.
    • Error in inter-rater reliability can occur due to scoring and interpretation.

    Reliability Methods

    • Test-retest reliability involves administering the same test to the same group of people on two separate occasions.
    • This method has one form and two testing sessions, with statistical treatment using Pearson-R correlation coefficient to calculate the reliability coefficient.
    • Error in test-retest reliability can occur due to test administration.

    Alternate-Forms Reliability

    • Alternate-forms reliability has two forms of a test, which helps to eliminate the issue of memorization.
    • Immediate alternate-forms reliability involves administering both forms to the same group of people at the same time.
    • This method has two forms and one testing session, with statistical treatment using Pearson-R correlation coefficient.
    • Error in immediate alternate-forms reliability can occur due to test construction or administration.

    Delayed Alternate-Forms Reliability

    • Delayed alternate-forms reliability involves administering the two forms with a time interval between them.
    • This method has two forms and two testing sessions, with statistical treatment using Pearson-R correlation coefficient.
    • Error in delayed alternate-forms reliability can occur due to test construction or administration.

    Internal Consistency Reliability

    • Internal consistency reliability can be measured using the split-half method or Cronbach's Alpha/KR-20 method.
    • The split-half method involves dividing the test into two halves and calculating the correlation between them using Pearson-R correlation coefficient and Spearman-Brown prophecy formula.
    • The Cronbach's Alpha/KR-20 method calculates the average correlation between all possible splits of the test.
    • Error in internal consistency reliability can occur due to test construction.

    Inter-rater Reliability

    • Inter-rater reliability measures the consistency of ratings or scores given by different raters.
    • This method involves administering the same test to the same group of people, with statistical treatment using the Kappa statistic.
    • Error in inter-rater reliability can occur due to scoring and interpretation.

    Reliability Methods

    • Test-retest reliability involves administering the same test to the same group of people on two separate occasions.
    • This method has one form and two testing sessions, with statistical treatment using Pearson-R correlation coefficient to calculate the reliability coefficient.
    • Error in test-retest reliability can occur due to test administration.

    Alternate-Forms Reliability

    • Alternate-forms reliability has two forms of a test, which helps to eliminate the issue of memorization.
    • Immediate alternate-forms reliability involves administering both forms to the same group of people at the same time.
    • This method has two forms and one testing session, with statistical treatment using Pearson-R correlation coefficient.
    • Error in immediate alternate-forms reliability can occur due to test construction or administration.

    Delayed Alternate-Forms Reliability

    • Delayed alternate-forms reliability involves administering the two forms with a time interval between them.
    • This method has two forms and two testing sessions, with statistical treatment using Pearson-R correlation coefficient.
    • Error in delayed alternate-forms reliability can occur due to test construction or administration.

    Internal Consistency Reliability

    • Internal consistency reliability can be measured using the split-half method or Cronbach's Alpha/KR-20 method.
    • The split-half method involves dividing the test into two halves and calculating the correlation between them using Pearson-R correlation coefficient and Spearman-Brown prophecy formula.
    • The Cronbach's Alpha/KR-20 method calculates the average correlation between all possible splits of the test.
    • Error in internal consistency reliability can occur due to test construction.

    Inter-rater Reliability

    • Inter-rater reliability measures the consistency of ratings or scores given by different raters.
    • This method involves administering the same test to the same group of people, with statistical treatment using the Kappa statistic.
    • Error in inter-rater reliability can occur due to scoring and interpretation.

    Non-Parametric Tests

    • Non-Parametric Tests do not rely on assumptions about underlying population parameters like mean, variance, which is required for parametric tests.
    • These tests are used to compare differences and correlations between groups.

    Types of Non-Parametric Tests

    Median Test

    • Compares the medians of 2 independent samples.
    • Only considers the number of cases above and below the median.
    • Uses ordinal data.
    • Applicable for 2 uncorrelated groups.

    Fisher's Sign Test

    • Compares 2 correlated samples by obtaining the differences between each pair of observation.
    • Considers the signs of the differences (above or below the median) between paired observations, not in their sizes.
    • Uses ordinal data.
    • Applicable for 1 correlated group.

    Wilcoxon Rank Sum Test

    • Used for comparing 2 independent samples using rank data.
    • Uses ordinal data.
    • Applicable for 2 uncorrelated groups.

    Mann-Whitney (U) Test

    • Used with independently drawn random samples, the sizes of which need not be the same.
    • Uses ordinal data.
    • Applicable for 2 uncorrelated groups.

    Wilcoxon Signed-Ranks Test (T)

    • Used for correlated samples, the difference, d, between each pair is calculated.
    • Data obtained is again subjected to computation.
    • Uses ordinal data.
    • Applicable for 1 correlated group.

    Kruskal-Wallis H Test

    • Used to test whether or not a group of independent samples is from the same or different population.
    • Compares three or more independent samples with respect to an ordinal variable.
    • Uses ordinal data.
    • Applicable for 2 or more uncorrelated groups.

    Friedman Rank Test

    • Used to test whether or not the data is from the same sample under 3 different conditions.
    • Uses ordinal data.
    • Applicable for 2 or more correlated groups.

    Non-Parametric Tests

    • Non-Parametric Tests do not rely on assumptions about underlying population parameters like mean, variance, which is required for parametric tests.
    • These tests are used to compare differences and correlations between groups.

    Types of Non-Parametric Tests

    Median Test

    • Compares the medians of 2 independent samples.
    • Only considers the number of cases above and below the median.
    • Uses ordinal data.
    • Applicable for 2 uncorrelated groups.

    Fisher's Sign Test

    • Compares 2 correlated samples by obtaining the differences between each pair of observation.
    • Considers the signs of the differences (above or below the median) between paired observations, not in their sizes.
    • Uses ordinal data.
    • Applicable for 1 correlated group.

    Wilcoxon Rank Sum Test

    • Used for comparing 2 independent samples using rank data.
    • Uses ordinal data.
    • Applicable for 2 uncorrelated groups.

    Mann-Whitney (U) Test

    • Used with independently drawn random samples, the sizes of which need not be the same.
    • Uses ordinal data.
    • Applicable for 2 uncorrelated groups.

    Wilcoxon Signed-Ranks Test (T)

    • Used for correlated samples, the difference, d, between each pair is calculated.
    • Data obtained is again subjected to computation.
    • Uses ordinal data.
    • Applicable for 1 correlated group.

    Kruskal-Wallis H Test

    • Used to test whether or not a group of independent samples is from the same or different population.
    • Compares three or more independent samples with respect to an ordinal variable.
    • Uses ordinal data.
    • Applicable for 2 or more uncorrelated groups.

    Friedman Rank Test

    • Used to test whether or not the data is from the same sample under 3 different conditions.
    • Uses ordinal data.
    • Applicable for 2 or more correlated groups.

    Correlation and Variables

    • A variable is anything that can change or vary
    • A correlation is a measure of the relationship between two or more variables

    Reliability

    • Test-retest reliability method: uses 1 form, 2 sessions, and Pearson-R statistical treatment to measure error in test administration
    • Alternate-Forms Immediate reliability method: uses 2 forms, 1 session, and Pearson-R statistical treatment to measure error in test construction or administration
    • Alternate-Forms Delayed reliability method: uses 2 forms, 2 sessions, and Pearson-R statistical treatment to measure error in test construction or administration
    • Internal Consistency - Split-Half reliability method: uses 1 form, 1 session, and Split-Half: Pearson-R and Spearman-Brown statistical treatment to measure error in test construction
    • Internal Consistency - Cronbach's Alpha - KR-20 reliability method: uses 1 form, 1 session, and Cronbach's Alpha or KR-20 statistical treatment to measure error in test construction
    • Inter-rater reliability method: uses 1 form, 1 session, and Kappa Statistic statistical treatment to measure error in scoring and interpretation

    Non-Parametric Tests

    • Non-Parametric Tests do not rely on assumptions about underlying population parameters (such as mean, variance) as is required for parametric tests
    • Median Test: used for comparing the medians of 2 independent samples, considers the number of cases above and below the median
    • Fisher's Sign Test: used for comparing 2 correlated samples, considers the signs of the differences (above or below the median) between paired observations, not in their sizes
    • Wilcoxon Rank Sum Test: used for comparing 2 independent samples using rank data
    • Mann-Whitney (U) Test: used for comparing 2 independent samples, the sizes of which need not be the same
    • Wilcoxon Signed-Ranks Test (T): used for comparing 2 correlated samples, calculates the difference, d, between each pair
    • Kruskal-Wallis H Test: used to test whether or not a group of independent samples is from the same or different population (i.e. compares three or more independent samples with respect to an ordinal variable)
    • Friedman Rank Test: used to test whether or not the data is from the same sample under 3 different conditions

    Correlation Coefficient

    • Correlation Coefficient (r) is a numerical value that represents the strength and direction of a relationship between two variables.
    • The Correlation Coefficient is a derived value, calculated using a specific formula to measure the correlation between two variables.

    Correlation

    • In a positive correlation, an increase in one variable is accompanied by an increase in the other variable.
    • Example: Perfectionism and test anxiety are positively correlated, meaning that as perfectionism increases, test anxiety also tends to increase.
    • In a negative correlation, an increase in one variable is accompanied by a decrease in the other variable.
    • Example: There is a negative correlation between cigarette smoking and life expectancy, meaning that as cigarette smoking increases, life expectancy tends to decrease.

    Correlation

    • A correlation is a measure of the relationship between two or more variables.
    • Correlation Coefficient (r) is a number that represents the strength and direction of a relationship between two variables.
    • Positive Correlation: as one variable increases, the other variable also increases.
    • Negative Correlation: as one variable increases, the other variable decreases.
    • The strength of a correlation is determined by how close the correlation coefficient is to +1.00 or -1.00.

    Reliability

    • Reliability is a measure of the consistency of a test or measurement.
    • There are several methods to measure reliability, including:
      • Test-retest: measures the consistency of a test over time.
      • Alternate-Forms Immediate: measures the consistency of different forms of a test.
      • Alternate-Forms Delayed: measures the consistency of different forms of a test over time.
      • Internal Consistency: measures the consistency of a test within itself.
      • Inter-rater: measures the consistency of ratings between different raters.
    • Each method uses a specific statistical treatment to calculate the reliability coefficient.

    Non-Parametric Tests

    • Non-Parametric Tests do not rely on assumptions about underlying population parameters, such as mean and variance.
    • These tests are used for ordinal data and can be used to compare differences or correlations between groups.
    • Some common Non-Parametric Tests include:
      • Median Test: compares the medians of two independent samples.
      • Fisher's Sign Test: compares two correlated samples by obtaining the differences between each pair of observation.
      • Wilcoxon Rank Sum Test: compares two independent samples using rank data.
      • Mann-Whitney (U) Test: compares two independent samples using rank data.
      • Wilcoxon Signed-Ranks Test (T): compares two correlated samples by obtaining the differences between each pair of observation.
      • Kruskal-Wallis H Test: compares three or more independent samples with respect to an ordinal variable.
      • Friedman Rank Test: compares two or more correlated samples with respect to an ordinal variable.

    Correlation

    • A correlation measures the relationship between two or more variables.
    • The correlation coefficient (r) is a number that represents the strength and direction of a relationship between two variables.
    • A positive correlation occurs when one variable increases as the other variable increases.
    • A negative correlation occurs when one variable increases as the other variable decreases.
    • The strength of a correlation is measured by its distance from +1.00 or -1.00, with correlations closer to +1.00 or -1.00 indicating stronger relationships.

    Reliability

    • Reliability refers to the consistency of a measure or test.
    • There are five types of reliability methods:
      • Test-retest reliability
      • Alternate-Forms Immediate reliability
      • Alternate-Forms Delayed reliability
      • Internal Consistency (Split-Half and Cronbach's Alpha) reliability
      • Inter-rater reliability
    • Each method has its own specific statistical treatment and error source.

    Non-Parametric Tests

    • Non-parametric tests do not rely on assumptions about underlying population parameters (such as mean, variance) as required for parametric tests.
    • Non-parametric tests are used with ordinal data.
    • Examples of non-parametric tests include:
      • Median Test
      • Fisher's Sign Test
      • Wilcoxon Rank Sum Test
      • Mann-Whitney (U) Test
      • Wilcoxon Signed-Ranks Test (T)
      • Kruskal-Wallis H Test
      • Friedman Rank Test
    • Each test has its own specific use and special note.

    Measures of Central Tendency

    • Statistics that indicate the average or midmost score between the extreme scores in a distribution.

    Types of Central Tendency

    • Mean: suitable for interval and ratio data with normal distribution.
      • Influenced by extreme values in the data.
      • Represents the "point of balance" of the distribution.

    Alternative Measures

    • Median: used when the distribution is skewed.
      • Represents the middle score of the population.

    Mode

    • Mode: the most frequently occurring score in a distribution.
      • The most recurrent number in the distribution.
      • Easiest to obtain among the measures of central tendency.

    Measures of Variability

    • Standard Deviation (s or σ) represents an approximation of the average deviation around the mean.
    • It provides details about how much individual scores deviate from the mean, indicating whether they are above or below it.

    Variance

    • Variance (s² or σ²) is calculated as the square of the standard deviation.
    • If the standard deviation (s) is 6, the variance (s²) would be 36, which is the square of 6.

    Understanding Standard Deviation (SD)

    • The average IQ has a mean of 100 and a standard deviation (SD) of 15.
    • One standard deviation above the mean is 100 + 15 = 115.
    • One standard deviation below the mean is 100 - 15 = 85.
    • The average range for IQ is between 85 and 115.

    Studying That Suits You

    Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

    Quiz Team

    More Like This

    Use Quizgecko on...
    Browser
    Open
    Browser
    Browser