Unit: Inference for Categorical Data: Chi – Square Chapter: Chi- square Test for Goodness of Fit Reference: – Categorical data, expected frequencies, Null & Alternative Hypothesis, Chi – square test statistics, Degrees of freedom, Critical value & P value, Decision rule, Interpretation, Assumptions & Conditions, Practical Application. After studying this chapter, you should be able […]
Unit: Inference for Categorical Data: Chi – Square Chapter: Chi- square Test for Homogeneity Reference: – Categorical Data, Contingency tables, Expected & Observed frequencies, Hypothesis testing, Degree of freedom, Chi- square Statistics, Critical value, P value, Assumptions & Interpretations, Applications. After studying this chapter, you should be able to: Categorical Data & Contingency Tables. Hypothesis […]
Unit: Inference for Categorical Data: Chi Square Chapter: Chi – Square Test for Independence Reference: – Exploring data, Sampling & Experimental design, Probability, Inference, Confidence Intervals, Power & Sample size, Designing Studies, bivariate data, Probability models, Chi- square tests, Inference for categorical data, Inference for Means & Proportions, Multivariate data analysis. After studying this chapter, […]
Unit: Inference for Categorical Data: Chi Square Chapter: Appropriate Inference Procedure Reference: – Exploring data, Sampling & Experimental design, Probability, Inference, Confidence Intervals, Power & Sample size, Designing Studies, bivariate data, Probability models, Chi- square tests, Inference for categorical data, Inference for Means & Proportions, Multivariate data analysis. After studying this chapter, you should be able […]
Unit: Inference for Categorical Data: Proportions Chapter: Constructing & Interpreting Reference: – Measures of center & Spread, Graphical displays, Measuring Associations, Residual Analysis, Probability Distributions, Sampling & Experimental Design, Inference for Categorical data, Interpreting Confidence Intervals, Bias & confounding, Simulation & Randomization, Sample Surveys. After studying this chapter, you should be able to: Measures of […]
Unit: Inference for Categorical Data: Proportions Chapter: Interpreting P-Values & Population Proportion Reference: – Hypothesis Testing, Interpreting P values, Strength of Evidence, Confidence Intervals, comparing two population proportion, Chi- square test proportion, Interpreting Practical Significance, Application & Case studies. After studying this chapter, you should be able to: Hypothesis Testing & Interpreting P Values. Confidence […]
Unit: Inference for Categorical Data: Proportions Chapter: Type 1 & Type 2 Errors Reference: – Error, false Positive, Probability of making error, Critical Value, Rejection region, False Negative, Factors affecting Type 1 & type 2 errors, Z- tests & t- tests, One tailed & two tailed tests. After studying this chapter, you should be able […]
Unit: Inference for Categorical Data: Proportions Chapter: Type 1 & Type 2 Errors Reference: – Error, false Positive, Probability of making error, Critical Value, Rejection region, False Negative, Factors affecting Type 1 & type 2 errors, Z- tests & t- tests, One tailed & two tailed tests. After studying this chapter, you should be able […]
Unit: Inference for Quantitative Data: Slopes Chapter: Confidence Intervals for the Slope of a regression model Reference: – Simple linear regression model, Least squares estimation, Interpreting the slopes, Sampling distribution of the slope, Standard error & Confidence interval for the slope, Hypothesis testing for slope, Degree of Freedom, Critical value & P value approach, Residual […]
Unit: Inference for Quantitative Data: Slopes Chapter: Setting up & Carry the Testing for regression model Reference: – Regression Analysis, Scatterplot, Hypothesis testing in Regression, Coefficient of determination, Residual Analysis & Diagnostics, Analyzing scatterplot & Variance, Influential Points & Outliers, Transformation, Model Comparison & Selection, Multicollinearity, ANOVA for Regression. After studying this chapter, you should […]