OKstate BADM 2233 Exam #2
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| Based on the normal distribution for this exam what percentage of students will score below the mean | 50%
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| nterpret the correlation r+ .95 | Strong Positive Relationship
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| Dispersion is a single value that represents a center point in the distribution | False
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| Common Variance | Variance shared with other variables. The measure of a linear area. We square the correlation to find common variance
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| Skewed Distribution | A representation of scores that lack symmetry around their average value
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| Leptokurtic | Scores that are bunched up toward the center of the distribution
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| Platykurtic | Fewer Scores in the middle of the distribution and more variation
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| Normal Distribution | A bell-shaped curve, describing the spread of a characteristic throughout a population
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| What percentage of values would we expect above a Z score of 0.0 | 50%
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| The sum of deviations from the mean will always equal what? | Zero
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| (T/F) We can have a negative variance value | False
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| A Gaussian curve is another name for what? | Normal Distribution
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| The most frequently occurring observation is called what? | Mode
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| The term bivariate means what? | 2 Variables
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| What do we call the center point of the distribution? | Median
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| The difference between the largest and smallest numbers? | Range
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| What percent of scores are represented by the whole of normal distribution? | 100%
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| Is it possible to have negative z-scores | yes
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| What do we call the arithmetic average? | Mean
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| Correlation | Examines the relationships between multiple variables within a single example.
Commonly used for prediction, once we have found that a relationship exists, we can predict an outcome
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| Bivariate | A set of data that has 2 variables
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| Data strength | Scores closer to -1 or 1 are stronger than scores closer to 0
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| Direction | +,-, or no correlation
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| Linear Relationship | The data is best described as a straight line
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| Non-linear relationship | A relationship between 2 variables that does not produce a straight line on a graph
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| Curvilinear relationship | A relationship between two variables whereby the strength and/ore direction of their relationship changes over the range of both variables
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| Heterogeneity | Great variation of outcomes (larger correlations)
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| Homogeneity | Data with similar outcomes (Smaller correlations)
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| Correlation | A measure of the extent to which 2 factors vary together, and thus of how well either factor predicts the other
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| Causation | A cause and effect relationship in which one variable controls the changes in another variable
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| Mode | The most frequent score in distribution
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| Median | Center point in a distribution (50th Percententile)
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| Mean | Arithmetic average of a distribution
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| Positive skew | Skewed to the left of the distribution
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| Negative Skew | Skewed to the right of the distribution
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| Kurtosis | How bunched up the scores are within the middle of the distribution
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| Dispersion | aThe pattern of spacing among individuals within the boundaries of the population
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| Range | Distance from the largest to smallest
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| Variance | The average of the squared differences from the mean
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| Standard Deviation | The square root of the variance
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| Normal Curve Characteristics, | Symmetric, bell shaped, inflection points, x axis is scores, y axis is frequency
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| Z-Score | A measure of how many standard deviations you are away from the mean
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| Z scores are represented in which units? | Standard Deviations
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| The Pearson correlation is good for evaluation curvilinear relationships | False
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| The degree to which the data are grouped together in the center or pushed to the edges of the distribution is referred to as what | Kurtosis
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| What is presented on the y axis mod the normal curve? | Frequency
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| How is the standard deviation calculated | Square root of the variance
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| Interpret the correlation R=-.050 | Moderately negative relationship
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| The term describes the average squared deviation from the mean | Variance
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