Report on LEVELS OR SCALES OF MEASUREMENT.pptx
- 1. LEVELS OR SCALES OF MEASUREMENT Level/Scale Characteristics Example 1. Nominal Nominal variables (also called categorical variables) can be placed into categories. They don’t have a numeric value and so cannot be added, subtracted, divided or multiplied. They also have no order No. reflected at the back shirts of the athletes 2. Ordinal The ordinal scale contains things that you can place in order. Ranks 3. Interval An interval scale has ordered numbers with meaningful divisions. Temperature is on the interval scale: a difference of 10 degrees between 90 and 100 means the same as 10 degrees between 150 and 160 4. Ratio Has all thecharacteristics of the interval scale except that it has an absolute zero point Height, weight *a zero weight means no weight at all
- 2. SHAPES, DISTRIBUTIONS AND DISPERSION OF DATA 1. SYMMETRICALLY SHAPED TEST SCORE DISTRIBUTION A. Normal Distribution or Bell Shaped Curve Frequencies Test Scores
- 3. SHAPES, DISTRIBUTIONS AND DISPERSION OF DATA 1. SYMMETRICALLY SHAPED TEST SCORE DISTRIBUTION A. Rectangular Distribution Test Scores Frequencies
- 4. SHAPES, DISTRIBUTIONS AND DISPERSION OF DATA 1. SYMMETRICALLY SHAPED TEST SCORE DISTRIBUTION A. U-shaped Curve Test Scores Frequencies
- 5. SHAPES, DISTRIBUTIONS AND DISPERSION OF DATA 2. SKEWED DISTRIBUTIONS OF TEST SCORES A. Positively Skewed Distribution B. Negatively Skewed Distribution Scores No. of Students Scores
- 6. What is Variability in Statistics? Variability (also called spread or dispersion ) refers to how spread out a set of data is. Variability gives you a way to describe how much data sets vary and allows you to use statistics to compare your data to other sets of data.
- 7. The four main ways to describe variability in a data set are: • RANGE • INTERQUARTILE RANGE • VARIANCE • STANDARD DEVIATION
- 8. MEASURES OF VARIABILITY A. Range B. Standard deviation C. Quartile Deviation or Semi- interquartile Range
- 9. DESCRIPTIVE STATISTICS • The first step in data analysis is to describe or summarize the data using descriptive statistics.
- 10. What is Variability in Statistics? Variability (also called spread or dispersion ) refers to how spread out a set of data is. Variability gives you a way to describe how much data sets vary and allows you to use statistics to compare your data to other sets of data.
- 11. I. MEASURES OF CENTRAL TENDENCY -numerical values which describe the average or typical performance of a given groups in terms of certain attributes. -basis in determining whether the group is performing better or poorer than the other groups.
- 12. Descriptive Satistics When to use and characteristics a. Mean Arithmetic average, use when the distribution is normal/symmetrical or bell shaped. Most reliable/stable b. Median Point in a distribution above and below which are 50% of the scores/ cases; medpoint of a distribution; use when the distribution is skewed c. Mode Most frequent/ common score in a distribution
- 13. II. MEASURES OF VARIABILITY - Indicate or describe how spread the scores are. The larger the measures of variability the more spread the scores are and the group is said to be heterogeneous; the smaller the measure of variability the less spread the scores are, the group is said to be homogenous.
- 14. MEASURES OF VARIABILITY A. Range-difference between the highest and lowest score; counterpart of the mode is also reliable and unstable B. Standard deviation-The counterpart of the mean, used also when the distribution is normal or symmetrical; Reliable/stable and widely used C. Quartile Deviation or Semi-interquartile Range- Defined as one- half of the difference between quartile 3(75th percentile) and quartile 1 (25th percentile) in a distribution; Counterpart of the median; Used when the distribution is skewed
- 15. III. Measures of Relationship -describe the degree of relationship or correlation between twovariables (academic achievement and motivation). It is express in terms of correlation coefficient from -1 to 0 to 10.
- 16. a. Pearson r b. Spearman-rank- order Correlation or Spearman Rho
- 17. IV. Measure of Relative Position -indicate where the score is in relation to all other scores in the distribution; they make it possible to compare the performance of an individual in two or more different tests.
- 18. a. Percentile Ranks b. Standard Scores c. Stanine Scores d. T-Scores
Editor's Notes
- #2: Represent real-valued random variables whose distribution are not-known Heights of people Measurement errors Blood pressure salaries Standard deviation controls the spread of the distribution.
- #3: Probability- equally probable Uniform distribution- distribution that has constant probability Rolling a die
- #5: A pos. skew means that the extreme data results are larger. The mean will be larger than the median in skewed