6

Distributions -- 6. Continuous Probability Distributions -- 7. Sampling and Sampling Distributions -- 8

Trivariate (X_it, Y1_it, Y2_it) -- 4.6 SCMs Based on Multivariate Endogenous and Exogenous Variables -- 4.7

-Derivatives and Least Squares -- 2.6.More Calculus-Integrals and Cumulative Distribution Functions -- Vocabulary

Fundamental Concepts -- 6. Confidence Intervals -- 7. Hypothesis Testing with a Single Sample Mean -- 8

-Style Paragraph -- 3.6.Summary -- Problems -- 4.Normal Distribution and Standard Scores -- 4.1.Normal Distribution

. IV Dispersion: "From Here to Eternity" -- 6.Range, Variance, and Standard Deviation -- What is

. Measures of Dispersion. -- 5. The Normal Curve. -- Part II: INFERENTIAL STATISTICS. -- 6. Introduction to

Data Analysis -- 1.6.1.The Stem and Leaf Plot -- 1.6.2.The Box Plot -- 1.6.3.Comments -- 1.7.Bivariate

-- 3. Graphic presentation -- 4. Measures of central tendency -- 5. Measures of variability -- 6. The

6

-- Part IV. Dispersion: "From Here to Eternity -- 6. Range, Variance, and Standard Deviation -- Part V

. Estimation -- 5. Testing hypotheses : choosing a test statistic -- 6. Strengths and limitations of some

dispersion or measuring spread ; Lecture 5. Models of distributions: shapely families ; Lecture 6. The bell

proportions -- 6. What does "not significant" really mean? -- 7. Confidence intervals -- 8. How to test for

analysis -- 4. Analysing the right problem -- 5. Understanding the big information picture -- 6

. Sampling and Allocation -- 5. Inference and Confidence Intervals -- 6. Hypothesis Testing: Two t Tests -- 7

and Sampling Distributions. Ch. 5. Statistical Inference I: Confidence Intervals. Ch. 6. Statistical

. Percentiles and Standard Scores -- 4. Correlation -- 5. Other Correlation Topics -- 6. Introduction to

. Descriptive measures of location or central tendency -- 5. Measures of spread, symmetry and kurtosis -- 6