Levels of Measurement in Statistics

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Questions and Answers

In statistics, what does skewness refer to?

  • The square root of the average squared deviations about the mean
  • The nature and extent to which symmetry is present in a distribution (correct)
  • The division of points between the four quarters in a distribution
  • The measure of average variability in a distribution

What is true about Pearson's correlation coefficient when it relates two continuous variables?

  • It shows the strength and direction of the relationship between the variables. (correct)
  • It uses spearman rank-order correlation.
  • It is used when one variable is continuous and the other is ordinal.
  • It can only be between 0 and 1 inclusive.

What does the principle of least squares refer to in regression analysis?

  • The technique used to calculate the slope of the regression line.
  • The method of finding the best-fitting line through observed data points. (correct)
  • The process of determining the coefficient of determination.
  • The method of calculating standard deviation in residuals.

When comparing two independent groups using a t-test, what does having unequal variances imply?

<p>The two groups have different variability in their scores. (D)</p> Signup and view all the answers

What is the purpose of a one-way ANOVA in statistical analysis?

<p>To compare multiple independent groups. (C)</p> Signup and view all the answers

In a regression analysis, what does the standard error of estimate represent?

<p>The standard deviation of the residuals around the regression line. (C)</p> Signup and view all the answers

When transforming a distribution to resemble a normal curve, what process involves making the distribution asymmetric?

<p>Kurtosis (A)</p> Signup and view all the answers

What is the primary purpose of hypothesis testing in statistics?

<p>To assess whether observed data support a hypothesis about a population. (D)</p> Signup and view all the answers

What is the critical region in hypothesis testing?

<p>The area of extreme values that make it very unlikely to obtain results if the null hypothesis is true. (C)</p> Signup and view all the answers

When using a t-test for hypothesis testing, what factor determines whether equal or unequal variances should be assumed?

<p>The result of a Levene's test (A)</p> Signup and view all the answers

Which level of measurement has a true zero point?

<p>Ratio (D)</p> Signup and view all the answers

What type of statistics is used to provide a concise description of a collection of quantitative information?

<p>Descriptive Statistics (D)</p> Signup and view all the answers

What is the property of 'moreness' in a scale?

<p>Magnitude (A)</p> Signup and view all the answers

What is the purpose of post-hoc tests in ANOVA?

<p>To determine the significance of the mean differences (A)</p> Signup and view all the answers

What type of scale can take on any value within a range and has an infinite number of possible values?

<p>Continuous Scale (B)</p> Signup and view all the answers

What is the average of all the raw scores in a distribution?

<p>Mean (A)</p> Signup and view all the answers

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Study Notes

Scales of Measurement

  • Nominal: categorization based on one or more distinguishing characteristics, no quantitative distinctions between observations
  • Ordinal: involves rank ordering, no quantitative distinctions between observations
  • Interval: has equal intervals, no absolute zero point, used when there has an unknown or undetermined score
  • Ratio: has true zero point, easiest to manipulate

Measures of Central Tendency

  • Mode: the most frequently occurring score in the distribution
  • Median: the middle score of the distribution
  • Mean: the average of all the raw scores, affected by extreme scores
  • Relationship between Mode, Median, and Mean:
    • Symmetrical Distribution: Mean = Median = Mode
    • Positively Skewed Distribution: Mean > Median > Mode
    • Negatively Skewed Distribution: Mean < Median < Mode

Measures of Variability

  • Range: the difference between the highest and lowest scores
  • Quartile: dividing points between the four quarters in the distribution
  • Interquartile Range: the difference between Q3 and Q1
  • Semi-interquartile Range: equal to the interquartile range divided by 2
  • Standard Deviation: a measure of variability, equal to the square root of the variance
  • Variance: the arithmetic mean of the squared deviations about the mean

Normal Curve

  • Bell-shaped, smooth, and mathematically defined curve
  • Highest at its center, asymptotically approaching the axis
  • Tails: 2-3 standard deviations above and below the mean
  • Stanine: a method of scaling test scores on a nine-point standard scale
  • Linear Transformation: retains a direct numerical relationship to the original raw score
  • Skewness: the nature and extent to which symmetry is absent

Standard Scores

  • Standard Score: a raw score that has been converted from one scale to another
  • Z-Scores: the results of the conversion of a raw score into a number indicating how many SD units the raw score is below or above the mean
  • T-Scores: a scale with a mean set at 50 and a standard deviation set at 10

Hypothesis Testing

  • Null Hypothesis: states there is no change, difference, or relationship
  • Alternative Hypothesis: states there is a change, difference, or relationship
  • Alpha Level or Level of Significance: the probability that the test will lead to a Type I error
  • Critical Region: composed of extreme values that are very unlikely to be obtained if the null hypothesis is true

Correlation and Inference

  • Correlation Coefficient: a number that provides an index of the strength of the relationship between two things
  • Types of Correlation Coefficients:
    • Pearson R
    • Spearman Rho
    • Kendall's Coefficient
    • Phi or Fourfold Coefficient
    • Point-Biserial Correlation
    • Rank Biserial Correlation
    • Tetrachoric Correlation

Regression Analysis

  • Predicts the values of a dependent or response variable based on values of at least one independent or explanatory variable
  • Residual: the difference between an observed value of the response variable and the value of the response variable predicted from the regression line
  • Standard Error of Estimate: the standard deviation of the residuals in regression

Tests

  • T-Test (Independent): compares two groups, used when two groups are independent samples
  • T-Test (Dependent)/Paired Test: used when two groups are paired or matched
  • One-Way ANOVA: compares three or more groups, used when one IV and one DV
  • Two-Way ANOVA: used when two IV and one DV
  • Critical Value: reject the null and accept the alternative if obtained value > critical value
  • P-Value (Probability Value): reject null and accept alternative if p-value < alpha level

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