FOUNDATIONAL LEVEL COURSE Statistics for Data Science I

 FOUNDATIONAL LEVEL COURSE Statistics for Data Science I  

  1. introduced to large datasets
  2. introduced to various insights one can glean from the data
  3. basic concepts of probability
  4. discussion on Random variables.  

What you’ll learnVIEW COURSE VIDEOS 

  1. Create, download, manipulate, and analyse data sets.
    Frame questions that can be answered from data in terms of variables and cases.
    Describe data using numerical summaries and visual representations.
    Estimate chance by applying laws of probability.
    Translate real-world problems into probability models.
    Calculating expectation and variance of a random variable.
    Describe and apply the properties of the Binomial Distribution and Normal distribution.
  2. WEEK 1Introduction and type of data, Types of data, Descriptive and Inferential statistics, Scales of measurement
    WEEK 2Describing categorical data Frequency distribution of categorical data, Best practices for graphing categorical data, Mode and median for categorical variable
    WEEK 3Describing numerical data Frequency tables for numerical data, Measures of central tendency - Mean, median and mode, Quartiles and percentiles, Measures of dispersion - Range, variance, standard deviation and IQR, Five number summary
    WEEK 4Association between two variables - Association between two categorical variables - Using relative frequencies in contingency tables, Association between two numerical variables - Scatterplot, covariance, Pearson correlation coefficient, Point bi-serial correlation coefficient
    WEEK 5Basic principles of counting and factorial concepts - Addition rule of counting, Multiplication rule of counting, Factorials
    WEEK 6Permutations and combinations
    WEEK 7Probability Basic definitions of probability, Events, Properties of probability
    WEEK 8Conditional probability - Multiplication rule, Independence, Law of total probability, Bayes’ theorem
    WEEK 9Random Variables - Random experiment, sample space and random variable, Discrete and continuous random variable, Probability mass function, Cumulative density function
    WEEK 10Expectation and Variance - Expectation of a discrete random variable, Variance and standard deviation of a discrete random variable
    WEEK 11Binomial and poisson random variables - Bernoulli trials, Independent and identically distributed random variable, Binomial random variable, Expectation and variance of abinomial random variable, Poisson distribution
    WEEK 12Introduction to continous random variables - Area under the curve, Properties of pdf, Uniform distribution, Exponential distribution

  3. Reference Documents / Books

    Descriptive Statistics (VOL 1)

    DOWNLOAD

    Probability and Probability Distributions (VOL 2)

    DOWNLOAD

    Prescribed Books

    The following are the suggested books for the course:

    Introductory Statistics (10th Edition) - ISBN 9780321989178, by Neil A. Weiss published by Pearson

    Introductory Statistics (4th Edition) - by Sheldon M. Ross

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