Unit: Sampling Distributions Chapter: Sampling Distributions for Sample proportions & Means Reference: – Sample Proportion, Interpreting, Sample Distribution, Mean & Standard deviation, Normal distribution, Central limit theorem & Applications, Sample Means, Comparing Proportions, Interpreting p Values, Hypothesis Testing, Sample size & Sample Bias. After studying this chapter, you should be able to: Sample Proportion & […]
Unit: Exploring One – Variable Data Chapter: Categorical variation & Quantitative Variables Reference: – Categorical Data, Frequency Tables, Bar Charts, Pie charts, Two-way tables, Conditional Distributions, Simpson’s Paradox, Quantitative data, Stem & Leaf plot’s, Histograms, Measure of central tendency, Measures of Variability, Box plots, Scatter plots After studying this chapter, you should be able to: […]
Unit: Exploring One – Variable Data Chapter: Tables or Graph Representation & Interpreting statistics Reference: – Data type, Frequency Distribution, Measures of center, Measures of spread, Box plots, Scatter plots, Correlation, Regression Analysis, Bar graph & Pie chart, two-way tables & Contingency tables, Probability & Normal Distribution, Confidence Intervals, Hypothesis Testing, Inference for Means & […]
Unit: Exploring One – Variable Data Chapter: Normal Distribution Reference: – Data Distribution, Describing data, Central Tendency, Normal Distribution, Bell shaped curve, Symmetry, Empirical rule, Z- Scores & Percentiles, Normal Probability plots, Central Limit Theorem, Sampling Distribution, Hypothesis Testing, Confidence Intervals After studying this chapter, you should be able to: Normal Distribution, Symmetry & Empirical […]
Unit: Exploring Two – Variable Data Chapter: Represent & Statistics for 2 Categorical Variables Reference: – Two-way Tables, Constructing & Interpreting, Marginal & Conditional frequencies, Joint, Marginal & Conditional distribution, Segmented Bar chart & Stacked Bar chart, Relative Risk & Odds Ratio, Independence & Association of Data, Conditional Probability & Independence, Simpson’s Paradox, Categorical Data […]
Unit: Exploring Two – Variable Data Chapter: Bivariate quantitative data using scatter plots Reference: – Scatter plot construction, Correlation, Best fit line, Regression line, Strength of relationship, outliers, Causation, Residual plots, Influential points, Transformation, Interpreting scatter plots After studying this chapter, you should be able to: Introduction to Scatter plot construction, Correlation. Regression line & […]
Unit: Exploring Two – Variable Data Chapter: Associations & Interpreting Correlations Reference: – Correlation coefficient, Scatter plots, Causation vs correlation, Pearson correlation coefficient, Spearman rank correlation, Kendall’s Tau, Coefficient of determination, Confounding variables, Outliers, strength of correlation. After studying this chapter, you should be able to: Correlation coefficient & Scatter plots. Causation vs correlation & […]
Unit: Collecting Data Chapter: Planning study & Sampling Methods Reference: – Bias, Confounding & Randomization, Stratified sampling, Cluster sampling, Types of sampling methods & Explanation, Types of Data & Variables, Surveys, Double blind experiments, Interpreting & Communicating, Application & Non responsive Bias. After studying this chapter, you should be able to: Bias, Confounding & Randomization. […]
Unit: Collecting Data Chapter: Sources of Bias & Designing Experiment. Reference: – Types of Bias & their sampling methods, non-responsive bias, Minimization, Under coverage bias, Voluntary response bias, Response bias, Experimental design, Controlled Experiments, Causation vs Correlation, Sampling techniques & Validity, Ethical considerations, Bias in surveys & Experiments After studying this chapter, you should be […]
Unit: Probability, Random Variables & Probability Distributions Chapter: Simulation to Estimate Probabilities Reference: – Random Sampling, Simulation methods, Monte Carlo simulation, Probability models, Experimental design, Randomization, Event Probability estimation, Law of large numbers, confidence intervals, Hypothesis testing, Error & variability, Visualizing probabilities. After studying this chapter, you should be able to: Random Sampling & […]