Summary of STAT193 2.pdf - 4/02/2019 Map of STAT193...

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4/02/20191Map of STAT193 “Statistics in Practice”SectionWeeksTitle…containsA1 - 3Informal inference with 1 and2 variables; probabilityCritical thinking; variables; data display – bar charts,boxplots, histograms, scatterplots; summary statistics;probability definitions and rulesB4 - 7Formal inference: hypothesistesting with 1 variableBinomial and Normal probability distributions; estimation;sign test; t-test for a mean; Z-test for a mean; Central LimitTheoremC8 - 11Formal inference: hypothesistesting using 2 variablesChi-square test; ANOVA; t-test for 2 independent means;linear regressionD12ConsolidationRevision and exam techniques, past exam questions, linkingtopics1WeekLectureTitleSection A (Weeks 1 – 3)Informal inference with 1 and 2 variables; probability11Introduction to Statistics12Data; Sampling from populations; Administration13Background maths; Types of variable;One variable: categorical data and graphs21Informal inference from categorical graphs; Numerical data and graphs; Informal inference from numerical graphs22More numerical graphs, percentiles; Mean and standard deviation23Two variables– bivariate data31Exercises on bivariate graphs; Misleading statistics32Probability fundamentals33Conditional probability; Random variables2
4/02/20192WeekLectureTitleSection B (Weeks 4 – 7)Formal inference: hypothesis testing with 1 variable41Binomial distribution42Normal distribution43Inverse normal; standard normal distribution; standardising scores51Hypothesis testing procedure; Sign Test52Sign Test53Sign Test for paired differences61Introduction tot-distributions; Estimation; Confidence intervals62t-test for mean63t-test of a mean using iNZight; extension work on confidence intervals71t-test for paired differences; Type I and II errors72Distribution of the sample mean; Central Limit Theorem73Sample means with the CLT3WeekLectureTitleSection C (Weeks 8 – 11)Formal inference: hypothesis testing with 2 variables81Analysingtwovariables; chi-square test82Chi-square test II; causation83Big picture! Guest lecturers91ANOVA92ANOVA; confidence intervals93ANOVA assumptions and residuals101t-test for difference of two means102Correlation and linear regression103Linear regression; prediction111Linear regression: residuals112Linear regression: assumptions113Testing gradient of regression line4
4/02/20193Section A(Weeks 1 – 3)Informal inference with 1 and 2 variables;probability56Background maths you need1.Percentages ↔ decimals (proportions)4% = 0.04;0.3 = 30%2. Fractions== 25%;ଵ଴଴= 0.013.Number line (for negative nos. esp.)4.< ܽ݊݀ ≤,> ܽ݊݀ ≥signs5.Scientific notation193 000 = 1.93 × 10;3.1 × 10ିସ= 0.000316.Rounding2.39154 = 2.3923dp0.00812 = 0.01 (2dp)7.Substitution in formulaeܶ =௫̅ିఓ:When ݔ̅ = 8, ߤ = 2, ݏ = 6, ݊ = 4 then ܶ = 28.Plotting points on graph (scatterplot)9.BasicΣ(sigma) notationIf ݔ= 3, ݔ= 10, ݔ= 1, ݔ= 2 then∑ݔ=௜ୀଷ௜ୀଵ3 + 10 + 1 = 14
4/02/20194IntroductionA key idea behind Statistics is to make objective inference in the presence ofuncertainty

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