Podcast
Questions and Answers
What are the two main purposes of statistics?
What are the two main purposes of statistics?
Description and inference
What does 'magnitude' refer to in a scale of measurement?
What does 'magnitude' refer to in a scale of measurement?
Moreness
Which type of scale has the properties of magnitude, equal intervals, and an absolute zero?
Which type of scale has the properties of magnitude, equal intervals, and an absolute zero?
- Ordinal
- Interval
- Ratio (correct)
- Nominal
A histogram is a type of graph that uses bars to represent the frequencies of categorical data.
A histogram is a type of graph that uses bars to represent the frequencies of categorical data.
What is the difference between the mean and the median?
What is the difference between the mean and the median?
What is the purpose of a standard deviation?
What is the purpose of a standard deviation?
A positively skewed distribution has a tail extending to the right of the distribution.
A positively skewed distribution has a tail extending to the right of the distribution.
What is the difference between a norm-referenced test and a criterion-referenced test?
What is the difference between a norm-referenced test and a criterion-referenced test?
What is a scatterplot used for?
What is a scatterplot used for?
Flashcards
Scales
Scales
A set of numbers whose properties model the empirical qualities of the objects they are assigned.
Magnitude
Magnitude
The property of "moreness." A particular instance of the attribute represents more, less, or equal amounts of the given quantity than does another instance.
Equal Intervals
Equal Intervals
The difference between two points at any place on the scale has the same meaning as the difference between two other points that differ by the same number of scale units.
Absolute Zero
Absolute Zero
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Nominal Scale
Nominal Scale
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Ordinal Scale
Ordinal Scale
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Interval Scale
Interval Scale
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Ratio Scale
Ratio Scale
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Raw Score
Raw Score
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Frequency Distribution
Frequency Distribution
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Histogram
Histogram
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Bar Graph
Bar Graph
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Frequency Polygon
Frequency Polygon
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Percentile Rank
Percentile Rank
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Percentile
Percentile
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Measures of Central Tendency
Measures of Central Tendency
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Mean
Mean
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Median
Median
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Mode
Mode
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Variability
Variability
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Range
Range
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Interquartile Range
Interquartile Range
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Standard Deviation
Standard Deviation
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Variance
Variance
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Skewness
Skewness
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Kurtosis
Kurtosis
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Norms
Norms
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Normal Curve
Normal Curve
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Normal Distribution
Normal Distribution
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Standard Score
Standard Score
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Z-Score
Z-Score
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T-Score
T-Score
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Stanine
Stanine
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STEN
STEN
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Correlation Coefficient
Correlation Coefficient
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Pearson Correlation Coefficient
Pearson Correlation Coefficient
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Spearman's Rho
Spearman's Rho
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Point-Biserial Correlation
Point-Biserial Correlation
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Phi-Coefficient
Phi-Coefficient
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Study Notes
Chapter II: Introduction
- Statistics transforms data into information and practice, crucial for an information-based society.
- Understanding basic statistics is essential to avoid manipulation and ensure informed decision-making.
- Statistics is a critical mathematical discipline for processing data into meaningful information.
- Basic statistical knowledge empowers individuals to interpret data encountered in everyday life.
- Psychological conclusions about human behavior need statistical methods to derive valid conclusions.
- Data collection requires sampling from populations to minimize bias.
- Rigorous statistical analysis supports hypothesis testing.
- This chapter provides a refresher course on statistics and its use in psychological assessment.
Lesson Proper: Why Statistics?
- Statistics concisely describes observations, comparing them to one another.
- Logical conclusions about unobserved events can be drawn using statistics.
- Descriptive statistics describes data in a concise form
- Inferential statistics uses data from a segment to draw conclusions about a larger group
Measurement: Scales
- Scales assign numbers to characteristics following rules.
- Continuous scales measure continuous variables.
- Discrete scales categorize variables without numerical meaning.
- Scale properties include magnitude (more/less), equal intervals (same meaning using scale units), and absolute zero (absence of the characteristic.)
- Examples of psychological tests (IQ levels) rarely exhibit equal intervals or absolute zero points.
Types of Measurement Scales
- Nominal scale: categorizes objects.
- Ordinal scale: ranks objects but does not define differences between ranks.
- Interval scale: ranks objects with equal interval sizes but no absolute zero.
- Ratio scale: ranks objects with equal interval sizes and an absolute zero point.
Describing Data: Frequency Distributions & Graphic Forms
- Frequency distributions: show how often each score occurs.
- Graphic forms: represent data visually with Histograms, Bar Graphs, and Frequency Polygons.
Measures of Central Tendency
- Mean: The average score.
- Median: The middle score in a distribution.
- Mode: The most frequent score.
- Mean is the most commonly used measure for interval/ratio data.
- Median is more useful when few extreme scores exist in a data set.
- Mode is appropriate for nominal data though isn't very common
Measures of Variability
- Standard Deviation and Variance calculate data spread.
- Skewness measures symmetry.
- Kurtosis measures the peakedness.
- Range, Interquartile Range are also used to measure variablity.
Normal Curve
- The normal curve displays a bell-shaped distribution.
- Mean, median, and mode are all located at the peak.
- Standard deviation units measure distance from mean in either direction.
- A well-established theory describes the distribution patterns under ideal conditions and is useful for inferential testing.
Correlation
- Correlation measures the relationships between variables.
- Correlation coefficients (e.g., Pearson r, Spearman ρ) quantify the strength and direction of these relationships.
- A correlation does not imply causation. (Correlation does not equal causation).
- Positive, negative, and no correlation are indicative of the relationship between two variables.
Tests of Correlation
- Pearson r is commonly used to examine linear relationships between continuous variables.
- Spearman ρ measures the relationship between ranked data.
- Point-biserial correlation measures association when one variable is dichotomous (e.g., yes/no) and the other is continuous.
- Phi coefficient is used for two dichotomous variables.
Regression
- Regression is a procedure for predicting scores on one variable from scores on another.
- Multiple regression uses more than one predictor variable.
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