IIT Madras Stats 1 Lectures: Statistics for Data Science I
BSMA1002140 lectures10 weeks
Weeks
- Week 18 lecturesIntroduction & types of data - basic definitions · Introduction & types of data - understanding data · Introduction & types of data - classification of data · Introduction & types of data - scales of measurement · Statistics for data science 1 · Statistics for data science 1 · Spreadsheet formulae · Downloading & uploading spreadsheets
- Week 210 lecturesDescribing categorical data - frequency distributions · Describing categorical data - charts of categorical data · Describing categorical data - best practices while graphing data - 1 · Describing categorical data - best practices while graphing data - 2 · Describing categorical data - mode & median · Problems charts & tables · Problems misleading graphs · SUMIF in google sheets · VLOOKUP in google sheets · Practice Assignment Solutions
- Week 312 lecturesDescribing numerical data - frequency tables for numerical data · Describing numerical data - mean · Describing numerical data - median and mode · Describing numerical data - measures of dispersion- range · Describing numerical data - percentiles, quartiles, and interquartile range · Tutorial 1 · Tutorial 2 · Tutorial 3 · Tutorial 4 · Tutorial 5 · Tutorial 6 · Box plot Tutorial
- Week 413 lecturesAssociation between two variables - review of course · Association between two categorical variables - introduction · Association between two categorical variables - relative frequencies · Association between two numerical variables - scatterplot · Association between two numerical variables - describing association · Association between two numerical variables - covariance · Association between two numerical variables - correlation · Association between two numerical variables - fitting a line · Association between categorical & numerical variables · Tutorial 1 · Tutorial 2 · Tutorial 3 · Tutorial 7
- Week 514 lecturesPermutations & combinations - basic principles of counting · Permutations & combinations - factorials · Permutations & combinations - permutations: distinct objects · Permutations & combinations - permutations : objects not distinct · Permutations & combinations - combinations · Permutations & combinations - applications · Tutorial 1 · Tutorial 2 · Tutorial 3 · Tutorial 4 · Tutorial 4 · Tutorial 5 · Tutorial 6 · Statistics for data science I
- Week 613 lecturesProbability - basic definitions · Probability - events & basic operations on events · Probability - random experiment, same space events · Probability - properties of probability · Tutorial 1 · Tutorial 2 · Tutorial 3 · Tutorial 4 · Tutorial 5 · Tutorial 6 · Tutorial 7 · Statistics for data science - I · Statistics for data science - I
- Week 713 lecturesConditional probability - contingency tables · Conditional probability - conditional probability formula · Conditional probability - multiplication rule · Conditional probability - independent events · Conditional Probability - independent events: examples · Conditional probability - independent events: properties · Conditional probability - bayes' rule · Tutorial 1 · Tutorial 2 · Tutorial 3 · Tutorial 4 · Tutorial 5 · Tutorial 6
- Week 813 lecturesRandom variables - introduction · Random variables - application · Random variables - discrete & continuous random variable · Discrete random variables - probability mass function properties · Discrete random variables - graph of probability mass function · Discrete random variables - cumulative distribution function · Tutorial 2 · Tutorial 3 · Tutorial 4 · Tutorial 5 · Tutorial 6 · Statistics for data science I · Practice Assignment Solution
- Week 98 lecturesDiscrete random variable - Application · Expectation of a random variable · Expectation of a random variable - Properties of expectation · Variance of a random variable - Properties of variance · Variance of a random variable - Properties of variance · Standard deviation of a random variable · Practice Assignment Solutions · Expectation of Hypergeometric Random Variable
- Week 1010 lecturesBinomial distribution - Bernoulli distribution · Binomial distribution - IID Bernoulli trials · Binomial distribution - Distribution of Binomial random variable · Binomial distribution - Modeling situations as Binomial distribution · Binomial distribution - Expectation and variance of Binomial random variable · Tutorial 1 · Tutorial 2 · Tutorial 3 · Tutorial 4 · Tutorial 5
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