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Module Four: Statistical Inference
Module Four: Statistical Inference - Estimation (point estimators and confidence intervals): Estimating population parameters and margins of error Properties of point estimators, including unbiasedness and variability Logic of confidence intervals, meaning of confidence level and confiden..
Module Four: Statistical Inference - Estimation (point estimators and confidence intervals): Estimating population parameters and margins of error Properties of point estimators, including unbiasedness and variability Logic of confidence intervals, meaning of confidence level and confiden..Module Three: Anticipating Patterns
Probability: Interpreting probability, including long-run relative frequency interpretation 'Law of Large Numbers' concept Addition rule, multiplication rule, conditional probability, and independence Discrete random variables and their probability distributions, including binomial and ..
Probability: Interpreting probability, including long-run relative frequency interpretation 'Law of Large Numbers' concept Addition rule, multiplication rule, conditional probability, and independence Discrete random variables and their probability distributions, including binomial and ..Module Two: Sampling and Experimentation
Overview of methods of data collection: Census Sample survey Experiment Observational study Planning and conducting surveys: Characteristics of a well-designed and well-conducted survey Populations, samples, and random selection Sources of bias in sampling and surveys Samp..
Overview of methods of data collection: Census Sample survey Experiment Observational study Planning and conducting surveys: Characteristics of a well-designed and well-conducted survey Populations, samples, and random selection Sources of bias in sampling and surveys Samp..Module One: Exploring Data
Module One: Exploring Data - Constructing and interpreting graphical displays of distributions of univariate data: Dotplot, stemplot, histogram, cumulative frequency plot Center and spread Clusters and gaps Outliners and other unusual features Shape Summarizing distributions of univariate data: Mea..
Module One: Exploring Data - Constructing and interpreting graphical displays of distributions of univariate data: Dotplot, stemplot, histogram, cumulative frequency plot Center and spread Clusters and gaps Outliners and other unusual features Shape Summarizing distributions of univariate data: Mea..Random variable (r.v)
Let S be a sample space associated with a given random experiment. A real valued function X which assigns to each w i S, a unique real number, X( w i ) = x i is called a random variabl..
Corollary 1:
C(n,r) = C(n,n-r..
Combinations
The selection of a number of things taking some or all of them at a time are called combinations. The number of ways of selecting r things out of n dissimilar things is denoted by C(n, r) or n C r..
Combinations
Combinations - The selection of a number of things taking some or all of them at a time are called combinations. The number of ways of selecting r things out of n dissimilar things is denoted by C(n, r) or n C r..
Conclusion
In this chapter, we have learnt the application of permutations and combinations, the fundamental counting principle and relation between n C r and n P r..
First method:
P(n,r) is the number of permutations of n dissimilar things taken r at a time. These permutations can be divided into two groups. (i) Those not containing a particular thing l . (ii) Those containing a particular thing l . Taking out l from the given things, we have (n-1)..
P(n,r) is the number of permutations of n dissimilar things taken r at a time. These permutations can be divided into two groups. (i) Those not containing a particular thing l . (ii) Those containing a particular thing l . Taking out l from the given things, we have (n-1).. Result
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