Review1-2up - ¡ ¡ ¡ ¡ ¡ inference. 5. Measure of the...

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Unformatted text preview: ¡ ¡ ¡ ¡ ¡ inference. 5. Measure of the goodness or reliability of the sample. 4. Inference about population based on info in 3. Sample of population units. 2. Specification of Variables to be investigated 1. Clear specification population of interest Five Elements of a Statistical Problem (p. 8) Sample (p. 5) Variable (p. 4) Population (p. 4) (estimates, decisions) Statistics (p. 2, 3) , “mu” (p. 42) (p. 41) – The mode (p. 44) – Skewness and Symmetry (p. 45) – The median (p. 42-43) – Population Mean : – Sample Mean : – Where is the “middle”? Measure of Central Tendency (p. 40) 68-71, 78-79, ) Box-plots, outliers, scatter diagrams (p. 28–30, Graphical Methods:Stem/Leaf, Histograms, Types of Data (p. 8): Quantitative, Qualitative Chapter 2 : Descriptive (Communicate) and Inferential STA 2023 c B.Presnell & D.Wackerly - Review for Exam I ¡ ¡ ¡ Chapter 1 : 1 ¢ £ STA 2023 c B.Presnell & D.Wackerly - Review for Exam I ¤ 2 (p. 53) £ ¨ (p. 53) (p. 52) ¦ ¤ MORE variability. – Variance or standard deviation LARGE Std. Dev. : Variance : – POPULATION Std. Dev. : Variance : ¢ ¡ (p. 52) 3 mean standard deviation value (p. 65) ment of how likely or probable an occurrence is. Rare Events and Inference - requires the assess- Quartiles (p. 69) Percentiles (p. 64) Miscellaneous Empirical Rule (bell-shaped distns) “approx.” (p. 57) least”(p. 56) Tchebysheff’s Theorem (always works) “at score : Interpreting the mean and standard deviation STA 2023 c B.Presnell & D.Wackerly - Review for Exam I – SAMPLE ¡ ¡ ¢ – The range (p. 51) © How about Variability, Spread or Dispersion? £   ¢   £ £ ¤  ¦ §¥  ¡  ¢   ¢ ¢ £ ¦ STA 2023 c B.Presnell & D.Wackerly - Review for Exam I  ¡  ¡ ¡ ¡ ¡ ¡ ¦ 4 RB RW IW IB DW DB ¨ and £ ¨ £ Independent (p. 131, 133): ¢ ¢ § ¢ ¢ ¡ ¡ £ ¡ ¡ ¡ ¡ ¡ ¡ Intersection and Union of two events (p. 104) § ¡ ¦ ¢ How to find the probability of an event (p. 106) © Multiplicative Law (p. 128): ¢ ¨ ¨ Events (p. 105) £ £ Properties of Probabilities of Simple Events (p. 104) ¢ Conditional probability (p. 122) § ¡ ¨ £ ¡ ¡ ¡ , (p. 101) ¢ Sample Space, £ £ ¡ £ Additive Rule (p. 117): ¡ ¡ ¢ © ¨ ¡ ¨ ¨ © ¡ £ ¨ ¨ © Sample Point (p. 101) £ ¡ ¥ © £ ¡ § Probability (p. 102) ¢ ¡ Experiment (p. 100) ¢ Complement (p. 115) £ Chapter 3 : £ £ £ § ¡ ¤ Mutually exclusive (disjoint) (p. 118) ¨ ¡ © ¨ © © ¡ ¡ ¡ £ ¢ ¨ ¨ £ STA 2023 c B.Presnell & D.Wackerly - Review for Exam I £ ¡ ¦ £ £ £ £ © ¢ ¨ ¨ ¨ ¨ ¢ £ £ £ © 5 ¢ STA 2023 c B.Presnell & D.Wackerly - Review for Exam I ¨ ©  ¤ © £ © © ¡  © ¡ ¡ ¡ ¦ ¨ ¨ ¦ ¢ ¨ ¨ ¦ ©  © ¦ ¨ £ £  © © ¢ © ¡  ©  (2) (1) 6 (p. 174). – The standard deviation of £ ¢ © ¨ © ¡ § £ ¡¢ ¥ © ¡ ¢ © £ ¨ ¨ ¢ £ ¨ © ¡ ¦ £ ¨ £ ¢ ¤ ¡ § £ ¡ ¦ £ ¢ © ¨ ¨ ¡ £ £ ¢ § ¡ £ ¨ © ¦ £ ¢ ¡ ¦ £ ¨ ¨ ¨ £ ¨ ¨ ¨ § ¡ © £ £ £ ¡ © ¡ ¦ © ¤ © ¨  ¢ © ¢ £ – Variance (p. 174) ¦ ¢  ¡ § is © ¢ ¤ ¢ ¤ £ ¨ £ £ ¨ £ ¤ ¨ ¡ ¡ © ¡ ¢ § £ ¨ – Put the pieces together! – – ¢ © ¤ ¨ ¤ ¢ mutually exclusive ¤ – £ ¡ ¦ – Mean (p. 172) ¦ – ¤ – Probability Distribution (p. 169) © – £ ¢ § © ¡ ¡ ¦ © © Discrete Random Variables (p. 166) £ £ – HIV Example(like 3.109, p. 158) £ ¡ ¡ Continuous Random Variables (p. 166) ¢  ¨ © ¤ £¥ ¨ ? © Random Variable (p. 164) ¨ ¦ . What is £ £ and ¤ Chapter 4 : ¢ ¥ STA 2023 c B.Presnell & D.Wackerly - Review for Exam I £  ©  Know 7 ¨ ¢  STA 2023 c B.Presnell & D.Wackerly - Review for Exam I £ 8 £ £ © ¥ ¨ (p. 183) number of trials, £ If ¤ ¥ trials £ ¥ ¥ ¥ ¡ £ ¥ £ ¨ © – Variable of interest: £ for number of stays same trial to trial ¦ £ ¨ – Trials are independent ¥ £ ¦ © – ¥ on each trial £ or ¡ ¢£ £ –  identical trials ’s in ¤ –  (p. 179) ¥ Characteristics of a Binomial Random Variable ¦ ¡ STA 2023 c B.Presnell & D.Wackerly - Review for Exam I © ¡ §¨ £ £ ¤ ¡ £ ¡ : ¥ ¥ 9 ...
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