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STATISTICS 243 FORMULAS 1 Source: Rachel L. Webb, PSU, January 2018 Learning Center 1875 SW Park Avenue, Millar Library, Portland, OR 97201 503.725.4448 www.pdx.edu ...
new examples and problems. In addition, this edition includes new subsections on † The Pareto Distribution (subsection 5.6.2) † Prediction Intervals (subsection 7.3.2 ) † Dummy Variables for Categorical Data (subsection 9.10.2) † Testing the Equality of Multiple Probability Distributions (subsection 12.4.2) SUPPLEMENTAL MATERIALS
Note: textbooks and formula sheets interchange “r” and “x” for number of successes Chapter 5 Discrete Probability Distributions: 22 Mean of a discrete probability distribution: [ ( )] Standard deviation of a probability distribution: [ ( )] x Px x Px µ σµ =∑• =∑• − Binomial Distributions number of successes (or x ...
Learning Objectives: Calculate various measures of central tendency—mode, median, and mean. Select the appropriate measure of central tendency for data of a given measurement scale and distribution shape. Know the special characteristics of the mean that make it useful for further statistical calculations. What Is Central tendency?
Linear Regression Model. Population Version: Mean: PY x E ( Y ) E 0 E 1 x Individual: y E E x H. 0 1 i. where H is N ( 0 , V ) Sample Version: Mean: y ˆ b b x.
1 ••• Master List of Formulas Chapter 1 IntroduCtIon and desCrIptIve statIstICs NONE. Chapter 2 FrequenCy dIstrIbutIons In tables and Graphs Σx (Frequency) Σx n (Relative frequency) Σx n × 100 (Relative percent) Chapter 3 summarIzInG data: Center tendenCy µ= Σx N (Population mean) M = Σx n (Sample mean) M Mn w n = Σ × Σ (Weighted sample mean) Chapter 4 summarIzInG data: varIabIlIty
STATISTICAL TABLES 1 TABLE A.1 Cumulative Standardized Normal Distribution A(z) is the integral of the standardized normal distribution from −∞to z (in other words, the area under the curve to the left of z). It gives the probability of a normal random variable not being more than z standard deviations above its mean.
