Unit: Exploring Two – Variable Data Chapter: Linear Regression Models & Residual plots Reference: – Simple Linear Regression, Slope & Intercept, Residual & Residual Plots, Positive & Negative Residuals, Assumptions of Linear Regressions, Linearity & Normality, Influential points & Outliers, Transformations & Non-linear relationships, Coefficient of Determination, Model Assessment & Inference, Applications. After studying this […]
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 understand: Correlation coefficient & Scatter plots. Causation vs correlation […]
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 understand: Introduction to Scatter plot construction, Correlation. Regression line […]
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 One – Variable Data Chapter: Comparing Data Distribution with The 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 […]
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: 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: Graphical Representation – Histogram 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 & Proportion. After studying […]
Unit: Exploring One – Variable Data Chapter: Graphical Representation – Bar Chart 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 & Proportion. After […]
Unit: Probability & Rules Chapter: Random Event Probability Calculating Reference: – Central limit theorem, Sampling distributions, Conditions for applications, Normal distribution, Sample mean distribution, Sample proportion distribution, Calculations, Applications, Margin of error, Confidence intervals, Hypothesis testing, Examples. After studying this chapter, you should be able to: Introduction to Central Limit theorem & Sampling distributions. […]