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