Unit: Probability, Random Variables & Probability Distributions Chapter: Random Event Probability Calculating Reference: – Sample spaces & Events, Probability definitions & Rules, Complementary & Mutually exclusive events, Conditional probability, Independence & Dependence, Probability distributions, Law of large number & Simulations, counting principles, Expected value & Variance, Central Limit theorem. After studying this chapter, you […]
Unit: Probability, Random Variables & Probability Distributions Chapter: Random Variables & Probability Distributions Reference: – Random Variables & Its types, Discrete Probability distribution, Continuous probability distributions, Expected Value & Variance, Law of Large Number & Central limit Theorem, Sampling Distributions, Transformations, Joint Distributions, Independent Random Variables, Bivariate data, Probability Models. Probability Mass function, Mean & […]
Unit: Sampling Distributions Chapter: Variation in Statistics for Collected Samples Reference: – Sampling methods, Bias & Randomness, Variability & Spread, Sampling distribution, Central limit theorem, Standard errors, Confidence intervals, Margin of error, hypothesis testing, Variability & Sample size. After studying this chapter, you should be able to: Sampling Methods, Bias & Randomness. Variability, Spread & […]
Unit: Sampling Distributions Chapter: Central Limit Theorem 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. Normal distribution & […]
Unit: Sampling Distributions Chapter: Biased & Unbiased Point Estimates Reference: – Population & Sample, Point estimates & Parameters, Accuracy Bias, Unbiased point estimates, Interpreting & Comparing, Mean & Variance of sample means, Sample proportion & Bias, Maximum likelihood estimation, Methos of moments estimation, Sample size & estimation, Application & Examples. After studying this chapter, you […]
Unit: Inference for Quantitative Data: Slopes Chapter: Selecting an Appropriate Inference Procedure Reference: – Sampling methods & Bias, Confidence Intervals, Hypothesis testing, Type 1 & type 2 Errors, Paired data & Matched pair tests, Chi- squared tests, Regression & correlation, Residual Analysis, Comparing two & Multiple Means, non-parametric tests, Bootstrapping, Bias & variability, Applications. After […]
Unit: Inference for Quantitative Data: Means Chapter: Constructing and interpreting Reference: – Language and communication, Art and media, Data and statistics, Architecture and design, Literature and Textual Analysis, Science and Research, Cultural Studies, Historical analysis, Mathematics Logic, Film and media Production. After studying this chapter, you should be able to: Mathematics logic. Data and Statistics. […]
Unit: inference for Quantitative Data: Means Chapter: Setting up and carry the testing Reference: – Null and alternative hypotheses, significance level, One sample z-test and t-test, Two sample tests, Type 1 and Type 2 errors, p value interpretation, Critical value and rejection Regions, chi-square test, paired t-test. After studying this chapter, you should be able […]
Unit: Inference of Quantitative Data: Means Chapter: Interpreting P-values & Population means Reference: – p-value definition, small p-values, Statical significance, population mean interpretation, Directionality, Comparison to significance level, type 1 error, Practical significance, Interpreting p-values in context. After studying this chapter, you should be able to: P-value definition Statical significance. Directionality. Population mean interpretation. P-value […]
Unit: Inference for Quantitative Data: Means Chapter: Confidence intervals & Tests Reference: – Confidence intervals for means, Confidence intervals for proportions, Confidence intervals for Differences, Confidence intervals for Regressions, Hypothesis testing, comparing means, Comparing Proportions, Power and Sample Size. After studying this chapter, you should be able to: Confidence intervals for means. Confidence intervals for […]