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Questions and Answers
What does a significant R² value of 0.990 in the multiple regression analysis indicate about the predictor variables?
What does a significant R² value of 0.990 in the multiple regression analysis indicate about the predictor variables?
Which of the following statements is true regarding the impact of study time and IQ on exam scores based on the results?
Which of the following statements is true regarding the impact of study time and IQ on exam scores based on the results?
What does the term 't' refer to in the context of the regression analysis results presented?
What does the term 't' refer to in the context of the regression analysis results presented?
What is the primary difference between a deterministic model system and a probabilistic model system?
What is the primary difference between a deterministic model system and a probabilistic model system?
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What is meant by unsystematic variation in statistical studies?
What is meant by unsystematic variation in statistical studies?
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Which of the following best describes descriptive statistics?
Which of the following best describes descriptive statistics?
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In which type of study are extraneous variables controlled to ensure only the independent variable affects the dependent variable?
In which type of study are extraneous variables controlled to ensure only the independent variable affects the dependent variable?
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What distinguishes categorical variables from continuous variables?
What distinguishes categorical variables from continuous variables?
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What is a defining feature of correlational methods in research?
What is a defining feature of correlational methods in research?
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In quasi-experimental designs, what participant arrangement is typically not used?
In quasi-experimental designs, what participant arrangement is typically not used?
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Which type of categorical variable is characterized by categories that have a meaningful order?
Which type of categorical variable is characterized by categories that have a meaningful order?
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What distinguishes a ratio scale from an interval scale?
What distinguishes a ratio scale from an interval scale?
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Which of the following is a potential weakness of a between-subjects design?
Which of the following is a potential weakness of a between-subjects design?
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Which hypothesis predicts that there will be no difference between the groups being studied?
Which hypothesis predicts that there will be no difference between the groups being studied?
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What is a critical factor in determining whether to reject or fail to reject the null hypothesis?
What is a critical factor in determining whether to reject or fail to reject the null hypothesis?
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Which of the following is an example of a Type 1 error?
Which of the following is an example of a Type 1 error?
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What is the primary advantage of using a matched-pairs design in experiments?
What is the primary advantage of using a matched-pairs design in experiments?
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What does the median represent in a data set?
What does the median represent in a data set?
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Which measure of central tendency is least affected by outliers?
Which measure of central tendency is least affected by outliers?
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What is one major disadvantage of using the mean as a measure of central tendency?
What is one major disadvantage of using the mean as a measure of central tendency?
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What term describes any variable not being studied that can influence the outcome?
What term describes any variable not being studied that can influence the outcome?
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Which of the following correctly describes order effects in a within-subjects design?
Which of the following correctly describes order effects in a within-subjects design?
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What is a key purpose of counterbalancing in experimental design?
What is a key purpose of counterbalancing in experimental design?
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How is variance calculated in a data set?
How is variance calculated in a data set?
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What is a primary disadvantage of using variance as a measure of dispersion?
What is a primary disadvantage of using variance as a measure of dispersion?
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What does a positive Z-score signify about a data point?
What does a positive Z-score signify about a data point?
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Which test is used to assess whether a dataset is normally distributed?
Which test is used to assess whether a dataset is normally distributed?
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What does a low p-value (p < 0.05) in Levene's Test indicate?
What does a low p-value (p < 0.05) in Levene's Test indicate?
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In correlation analysis, what does a coefficient value of -0.9 indicate?
In correlation analysis, what does a coefficient value of -0.9 indicate?
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Which of the following is NOT an attribute of Spearman's Correlation Coefficient?
Which of the following is NOT an attribute of Spearman's Correlation Coefficient?
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What does the term 'Variance Explained' refer to in correlation studies?
What does the term 'Variance Explained' refer to in correlation studies?
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Which correlation measure is appropriate for continuous variables?
Which correlation measure is appropriate for continuous variables?
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In regression analysis, what is the predictor variable often referred to as?
In regression analysis, what is the predictor variable often referred to as?
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What does a first-order partial correlation do?
What does a first-order partial correlation do?
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What is the shape of a normal distribution?
What is the shape of a normal distribution?
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What signifies a zero-order correlation?
What signifies a zero-order correlation?
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Which statement is true regarding covariance?
Which statement is true regarding covariance?
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When conducting multiple regression analysis, what is the primary goal?
When conducting multiple regression analysis, what is the primary goal?
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Which of the following describes a key characteristic of a within-subjects design?
Which of the following describes a key characteristic of a within-subjects design?
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What is the main advantage of using a ratio scale compared to an interval scale?
What is the main advantage of using a ratio scale compared to an interval scale?
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In hypothesis testing, what does a Type 2 error indicate?
In hypothesis testing, what does a Type 2 error indicate?
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Which measure of central tendency is least influenced by extreme outliers?
Which measure of central tendency is least influenced by extreme outliers?
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What is a potential disadvantage of using a matched-pairs design in experiments?
What is a potential disadvantage of using a matched-pairs design in experiments?
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Which method is primarily concerned with examining associations between variables without the manipulation of any variables?
Which method is primarily concerned with examining associations between variables without the manipulation of any variables?
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What is a primary characteristic of a deterministic model system?
What is a primary characteristic of a deterministic model system?
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Which type of variable categorizes data into distinct groups with no order or hierarchy?
Which type of variable categorizes data into distinct groups with no order or hierarchy?
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What is the primary difference between experiments and quasi-experiments?
What is the primary difference between experiments and quasi-experiments?
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Which statistical technique is essential for summarizing and presenting the characteristics of a given data set?
Which statistical technique is essential for summarizing and presenting the characteristics of a given data set?
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Study Notes
Statistics and Scientific Methods
- Statistics is the process of identifying patterns in data, finding out about patterns in the world using real data.
- Deterministic models assume no randomness; outcomes are always the same with identical conditions.
- Probabilistic models incorporate randomness, resulting in varied outcomes even with consistent starting points.
- Unsystematic variation arises from unknown, uncontrolled factors (e.g., participant mood, intelligence, education). Random assignment of participants can limit this variation.
- Systematic variation results from manipulations of the independent variable.
- Descriptive statistics summarize data characteristics (central tendency, variability, frequency).
- Inferential statistics uses sample data to estimate larger population characteristics.
Scientific Methods
- Experiments investigate cause-and-effect relationships by manipulating an independent variable (IV) and measuring the dependent variable (DV), controlling extraneous variables. This requires control and treatment groups to avoid confounding variables.
- Quasi-experiments explore cause-and-effect but lack random assignment of participants to groups. Researchers have less control over conditions.
- Correlational methods examine the association between variables without manipulation or intervention; variables are only observed.
Variables
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Categorical variables classify data into distinct groups.
- Nominal variables have no inherent order (e.g., hair color).
- Ordinal variables have a meaningful order (e.g., educational level; discrete variables).
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Continuous variables can take on any value along a scale.
- Interval scales indicate equal differences but lack a meaningful zero point (e.g., temperature).
- Ratio scales have equal intervals and a meaningful zero point (e.g., height).
- Independent variable (IV) is the manipulated factor in an experiment, expected to affect the dependent variable (DV).
- Dependent variable (DV) is the measured outcome.
Experimental Designs
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Between-subjects design: different groups experience different conditions.
- Weaknesses: participant variability, time-consuming.
- Strengths: avoids practice effects, demand characteristics, and only has one condition.
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Within-subjects design: one group experiences all conditions.
- Weaknesses: order effects, carryover effects.
- Strengths: fewer participants, less participant variability.
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Matched-pairs design: participants matched based on a characteristic, each experiences different conditions.
- Strengths: reduces individual differences.
- Weaknesses: time-consuming, smaller sample size.
- Extraneous variables are uncontrolled variables potentially affecting results.
- Confounding variables systematically influence both the IV and DV.
Hypothesis Testing
- Hypothesis: a testable prediction.
- Alternative hypothesis: predicts a difference between groups.
- Null hypothesis: predicts no difference between groups.
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P-value: probability of observing results by chance.
- A low p-value (<0.05) suggests the null hypothesis is likely false.
- Type I error: incorrectly rejecting the null hypothesis (false positive).
- Type II error: incorrectly accepting the null hypothesis (false negative).
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Validity: accuracy of a test in measuring what it intends to measure.
- Internal validity: related to order, practice, boredom effects within an experiment.
- Ecological validity: generalizability to real-world situations.
- Demand characteristics: influence from participants' expectations.
- Reliability: consistency of a measure, including inter-rater reliability and test-retest.
Descriptive Statistics
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Central tendency: average value; measures central position.
- Mode: most frequent observation; can be used with categorical data.
- Median: middle observation; unaffected by extreme values; suitable for ordinal, interval, and ratio data.
- Mean: average of all values; uses all data; sensitive to extreme values.
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Measures of spread: variability around a central tendency.
- Range: difference between highest and lowest values; sensitive to outliers.
- Interquartile range (IQR): spread of the middle 50% of data; robust to outliers.
- Variance: average squared deviation from the mean; useful with normal distributions; sensitive to outliers; dimensionless.
- Standard deviation: square root of variance; same units as the original data; higher deviation indicates greater variability.
- Standard Error of the Mean (SEM): measure of how precisely a sample mean estimates the population mean.
- Z-scores: measure of how many standard deviations a data point falls from the mean.
- Normal distribution: symmetrical bell-shaped curve; mean=median=mode; common in many natural phenomena.
- Skewed distribution: majority of scores on one side
Statistical Tests
- Kolmogorov-Smirnov test: tests if data is normally distributed.
- Levene's test: tests for equality of variances between groups.
Correlation
- Correlation: measures the association between two variables.
- Covariance: measures the relationship between two random variables, influenced by measurement units.
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Correlation coefficient: indicates magnitude (-1 to +1) and direction of relationship.
- Pearson's correlation: uses continuous variables; assumes a linear relationship.
- Spearman's rank correlation: uses ranked data; good for ordinal data.
- Variance explained: squared correlation coefficient; percentage of variation in one variable explained by the other.
- Partial correlation: examines association controlling for other variables.
- Zero-order correlation: simple bivariate correlation.
- First-order/second-order partial correlation: examines relationships with one or more variables held constant.
Regression
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Regression analysis: predicts a variable (dependent variable) from other variables (independent variables).
- Linear regression: predicts a dependent variable from one independent variable using a straight line.
- Multiple regression: predicts a dependent variable from multiple independent variables.
- Reporting regression in APA: includes R-squared, F-statistic, p-value, t-tests for each predictor, unstandardized estimates (coefficients), and explanations of coefficients; describes how changes in IVs affect the DV. Explains significant relationships.
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Description
Test your understanding of key concepts in statistics and scientific methods. This quiz covers deterministic and probabilistic models, variations in data, and both descriptive and inferential statistics. Assess your knowledge of experimental design including control and treatment groups.
