Applied Statistics (2015)
Topic outline
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Forum
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1.1 Statistical Terminologies
1.2 Statistical Problem Solving Methodology
1.3 Review on Descriptive Statistics
1.3.1 Measures of Central Tendency
1.3.3 Measures of Position
1.3.2 Measures of Variation
1.3.2.1 Accuracy and Precision1.4 Exploratory Data Analysis
1.4.1 Stem and Leaf Plot
1.4.2 Outliers
1.4.3 Box Plot1.5 Normal Probability Plot
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2.1 Sampling Distributions
2.2 Estimate, Estimation, Estimator
2.3 Confidence Interval for the Population Mean
2.4 Confidence Interval for the Difference between Two Population Means
2.5 Confidence Intervals with Paired Data2.6 Confidence Interval for the Population Proportion
2.7 Confidence Interval for the Difference between Two Population Proportion
2.8 Confidence Interval for Population Variance and Population Standard Deviation
2.9 Confidence Interval on the ratio of Two Population Variances and Standard Deviations -
3.1 Introduction to Hypothesis Testing
3.1.1 Terms and Definitions
3.1.2 Procedure of Hypothesis Testing
3.2 Test Hypothesis for Population Mean with known and unknown Population Variance
3.3 Test Hypothesis for the Difference Population Means with known and unknown Population Variance3.4 Test Hypotheses for Paired Data
3.5 Test Hypotheses for Population Proportion
3.6 Test Hypotheses for the Difference between Two Population Proportions3.7 Test Hypotheses for Population Variance
3.8 Test Hypotheses for the Ratio of Two Population Variances
3.9 P-Values in Hypothesis Test
3.10 Relationship between Hypothesis Tests and Confidence Interval -
4.1 Introduction to ANOVA
4.2 One-Way ANOVA
4.3 Two-Way ANOVA
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5.1 Correlation
5.1.1 Scatter Plot
5.1.2 Pearson Product- Moment Correlation5.2 Coefficient of Determination
5.3 Simple Linear Regression
5.3.1 Estimation of the Model Parameters and Value Prediction
5.4 Hypothesis Testing for Simple Regression Model
5.4.1 Hypothesis Testing for Intercept
5.4.2 Hypothesis Testing for Slope
5.4.3 Hypothesis Testing for Slope using ANOVA
5.5 Multiple Linear Regression Analysis and Correlation
5.5.1 Multiple Linear Regression Equation
5.5.2 Computing the Multiple Linear regression model
5.5.3 Interpretations of Regression Statistical Output
5.6 Model Selection -
6.1 Goodness of Fit
6.1.1 Goodness of Fit Test for Categorical Data
6.1.2 Fitting of the Distribution
6.2 Contingency Table6.2.1 Test for Two Variable for Independence
6.2.2 Test of Homogeneity Proportions -
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