PSYC 203 1st Edition Lecture 4Outline of Last Lecture I. Review of last class a. Parameter vs. Statistics b. Sampling errorc. Formula for Mean II. Categorical dateIII. MedianIV. PercentileV. ModeVI. Distributions & Central TendencyVII. VariabilityVIII. RangeIX. Standard DeviationOutline of Current Lecture I. Review of last classII. MedianIII. VariabilityIV. Range without reference to real limits V. Standard deviation and variance VI. Standard deviation VS.varianceCurrent LectureI. Review of last class a. When the Mean is suboptimal:i. Categorical Data ii. Skewed DataII. Mediana. With an odd number of scores, list the values in order, and the median is the middle score in the list.i. Ex.: 8, 3, 5, 1, 6_1, 3, 5, 6, 8_Mdn = 5These notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute.b. With an even number of scores, list the values in order, and the median is half- way between the middle two scores.i. Ex.: 8, 3, 5, 1, 6, 9_1, 3, 5, 6, 8, 9_Mdn = 5.5III. Variabilitya. Describes how scores differ from one another i. How much each score in a group of scores differs from the meanii. 3 measures commonly used for this are:1. range2. standard deviation3. varianceiii. range is the most general measure IV. Range without reference to real limits a. Range= Xmax-Xminb. Kissing example: Max number of “people kissed” is 99 while the minimum is 0 so99-0=99, this is the range V. Standard deviation and variancea. Standard deviation is the avgamt of variability in a set of numbers, in other words, the average distance from the mean. b. ***It is important to first know whether you are solving for the mean or for the sample i. If solving for the population: To solve, first compute the deviation score for all observations in a dataset, so that the variance can be calculated 1. Deviation score= X-μa. SS (sum of squares) is the sum of the squared deviations ofscores from the mean – The Numerator of this Equation!i. To solve for SS(sum of squares): 1.b. SS (sum of squares) is the sum of the squared deviations ofscores from the mean – The Numerator of this Equation!ii. If solving for the sample: 1.c. also, note that the sum of deviations from the mean is always zero.d. square the deviations scores because we want to get ride of the negative sign s that when we sum them up we don’t get 0. In the standard deviation formula, we take the square root to get back to our original units. e. mean deviation: sum of the absolute value of the deviations from the mean VI. Standard deviation VS.variancea. Both measures of variability b. Standard dev. Is stated in its original units, while the variance is stated in units that are