Review1-4up - 1 STA 2023 c B.Presnell & D.Wackerly -...

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Unformatted text preview: 1 STA 2023 c B.Presnell & D.Wackerly - Review for Exam I STA 2023 c B.Presnell & D.Wackerly - Review for Exam I 2 Chapter 1 : Chapter 2 : ¡ Descriptive (Communicate) and Inferential (estimates, decisions) Statistics (p. 2, 3) ¡ ¡ Types of Data (p. 8): Quantitative, Qualitative Population (p. 4) ¡ ¡ Graphical Methods:Stem/Leaf, Histograms, Variable (p. 4) ¡ Sample (p. 5) ¡ Five Elements of a Statistical Problem (p. 8) Box-plots, outliers, scatter diagrams (p. 28–30, 68-71, 78-79, ) ¡ Measure of Central Tendency (p. 40) – Where is the “middle”? (p. 41) – Population Mean : 3. Sample of population units. ¤ – Sample Mean : 2. Specification of Variables to be investigated ¢£ 1. Clear specification population of interest , “mu” (p. 42) – The median (p. 42-43) 4. Inference about population based on info in – Skewness and Symmetry (p. 45) sample. – The mode (p. 44) 5. Measure of the goodness or reliability of the inference. 3 STA 2023 c B.Presnell & D.Wackerly - Review for Exam I STA 2023 c B.Presnell & D.Wackerly - Review for Exam I Interpreting the mean and standard deviation ) 10¡ – The range (p. 51) (p. 65) Empirical Rule (bell-shaped distns) “approx.” (p. 57) Miscellaneous ¡ Percentiles (p. 64) Quartiles (p. 69) ¡ Rare Events and Inference - requires the assess- ¦ ¦ # $!  § " ¨ ¦   ¨ ©§ (p. 53) (p. 53) ¥ ¥ ( § % % #! '§ & ¨ % ¥ ¥ – Variance or standard deviation LARGE MORE variability. standard deviation ¡  Std. Dev. : mean least”(p. 56) (p. 52) (p. 52) – POPULATION Variance : value Tchebysheff’s Theorem (always works) “at ¡  Std. Dev. : ¢  § £ £  Variance : ¡ – SAMPLE score :  How about Variability, Spread or Dispersion? ment of how likely or probable an occurrence is. 4 ¡ 5 STA 2023 c B.Presnell & D.Wackerly - Review for Exam I STA 2023 c B.Presnell & D.Wackerly - Review for Exam I ¡ ¡ ¡ ¡ Probability (p. 102) ¡ Sample Point (p. 101) ¡ Sample Space, ¡ Properties of Probabilities of Simple Events (p. 104) ¡ Events (p. 105) ¨  ¡ £ Experiment (p. 100) ¡ How to find the probability of an event (p. 106) ¡ Intersection and Union of two events (p. 104) ¢  £   ¡  £ ¨  ¢ §¡  £ ¦ ¡ Additive Rule (p. 117): ¡ Conditional probability (p. 122)  ¢ ©¡  £ ¡ Multiplicative Law (p. 128):  #  ¡  £  ©¡ ¢  ¨  ¢   ¢ ¡  ¨  ¢ §¡  ©£ ¨£ £ £ IW ¡ RB DB IB ¢ STA 2023 c B.Presnell & D.Wackerly - Review for Exam I 7 STA 2023 c B.Presnell & D.Wackerly - Review for Exam I Chapter 4 : – Mean (p. 172) – Variance (p. 174) % %£ § !¨  £  # §  ¤ £   ¨ §  ¤ £  &"©§ %   %!¨ ' ¤ ¢ ¤ ¢ £ ¡ £ £ – Put the pieces together!  £ – – Probability Distribution (p. 169) !¤  ¨ £  "¨   © ¨ £ ¤ ¢ ¡  £ ¨ ¤ ¢ §¡  ¨¡  £   ¢ §¡  £ ¨  ¡  ¨     ¤ ¢ ¡  ¦  ¢ ¡  ¨ ¨ ¨ © ¢   ¢ ¡  ¨  ¢ §¡  ¨ £  ¡ £ #  ¢ §¡ £  ¨  ©¡ ¢  ¨£ – mutually exclusive Discrete Random Variables (p. 166) # £  $£  ¢ ¡  ©£ – Continuous Random Variables (p. 166) ¡  ¤ ¢ ¡  ©£ – Random Variable (p. 164) ¡ . What is – HIV Example(like 3.109, p. 158) –  ©¡ ¢  £ ? and ¡ Know (2) Independent (p. 131, 133): DW ¨ §¡  £ ¥ ©¡ ¢  £ ¥ ¢ ©¡  ¥ £¡ ¢ ¡ RW and (1) #  ¢  £  ¡  ¨  ¢  ¢ £ ¨   ¡ £ ¨  £ , (p. 101)  ¢ #  ¢ §¡ £  ¨ ¨£ ¨ #  ¢ §¡  £   ¤ #  ¥¡  £   Chapter 3 : Mutually exclusive (disjoint) (p. 118) Complement (p. 115) 6 – The standard deviation of (p. 174). is 8 ¡ STA 2023 c B.Presnell & D.Wackerly - Review for Exam I 9 ¡ Characteristics of a Binomial Random Variable (p. 179)   # £¨ – identical trials or –  – on each trial stays same trial to trial – Trials are independent ¨£ ¨ (p. 183) for  ¡ # # # ¡  ¡ ¨ £  number of trials, ’s in #   ¨ ¢¢# ¨   £¡ £ If trials number of  – Variable of interest: : ¨£ ¨ §©# ¦ §£  ¤  ¥¨ £  # ¡ ...
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This note was uploaded on 12/15/2011 for the course STA 2023 taught by Professor Ripol during the Spring '08 term at University of Florida.

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