Statistics and Probability for Data analytics & Data science

Statistics and Probability for Data analytics & Data science free download

Master your foundations in Statistics and probability for data insights in the field of Data analytics and Data science

Unlock the power of data with our comprehensive course: Statistics and Probability for Data Analytics & Data Science. In an era where data is the new oil and data drives decision-making, mastering these foundational concepts is of core importance for anyone looking to excel in the field of data analytics, business analytics or data science.

So, anyone who want to acquire these necessary skills for a bright career prospect in these fields, then, you’ve come to the right place my friend!

This 45 chapters course will help you to master your foundations in the field of statistics and probability which will help you to take data driven decisions appropriately. The course provides crisp yet comprehensive and detailed videos for every concept in the field of statistics and probability followed by quizzes with solutions to test the clarity of your concepts.

So, below is the overview of what we will be covering in this course:

• Fundamentals of statistics

• Deep dive into descriptive statistics including univariate data analysis with the help of levels of measurement, measures of central tendency, measures of variability and shape of distribution for proper data analysis

• Five-point summary and Outlier detection using box plot method

• Bi variate data analysis such as coefficient of deviation, covariance, correlation (including both Pearson correlation and spearman rank correlation), scatter plots, etc.

• Permutation and combination along with their various cases and examples

• Probability and its various concepts such as its set operations, dependent events, total probability and Bayes theorem

• Understanding discrete and continuous variable probability distributions including cumulative probability distributions

• Different probability distributions for both discrete and random variable such as Uniform, Bernoulli, Binomial, Poisson, Normal, Students T, Chi square and F.

• Use cases and examples of each probability distributions

• Sampling distributions of mean, margin of error, point estimate, confidence interval and its various cases for one sample and two sample

• Inferential statistics including hypothesis testing, one tailed and two tailed test, different test of mean, chi square and ANOVA testing

• Practical applications of one tailed and two tailed test

• Real life scenarios of type 1 and type 2 error for better clarity

So, enroll today guys and master your concepts in statistics and probability.