In this Statistics Course video Sumit Shukla, DSML Educator, will help you understand all about what is statistics, how statistics can be used in data science, what is probability, why statistics and probability is important in data science & decision making, what is hypothesis testing and much more. Check out free masterclasses by industry-leading experts here: https://www.scaler.com/events?utm_source=Youtube&utm_medium=osocial&utm_campaign=brand_scaler_events_osocial_youtube_probability-statistics-full-course-by-sumit-shukla&utm_content=YTDescription
Topics Covered:
0:00 - Introduction
1:07 - Statistics and it's types
24:13 - What are variables in Statistics - Qualitative & Quantitative
36:41 - Descriptive Statistics
58:50 - Measures of Dispersion (Variation)
1:26:56 - Coefficient of Variation
1:44:48 - Introduction to Probability
1:58:09 - Rules of Probability
2:20:20 - Dependent Events
2:40:05 - Random Variables
3:00:21 - Distributions
3:07:18 - Continuous Random Variable
3:16:40 - Discrete Random Variable (Bernoulli & Binomial)
3:20:07 - Binomial Expression
4:40:00 - Inferential Statistics
4:46:51 - Sampling
4:49:59 - Central Limit Theorem
5:06:52 - Hypothesis Testing
5:24:42 - Rules of Hypothesis Testing
5:30:50 - Types of Test: Z-Test & T-Test
6:30:24 - Error in Hypothesis Testing
What is statistics?
Statistics is a branch of mathematics and science that involves collecting, organizing, analyzing, interpreting, and presenting data. It is used to gain insights, make informed decisions, and draw conclusions about various phenomena.
What is probability?
Probability is a measure of the likelihood of an event occurring. It is expressed as a number between 0 and 1, with 0 indicating impossibility and 1 indicating certainty. Probability theory is used to quantify uncertainty and randomness in various fields, such as mathematics, science, and statistics.
What is hypothesis testing?
Hypothesis testing is a statistical method used to make inferences about population parameters based on a sample of data. It involves formulating a null hypothesis and an alternative hypothesis, collecting data, and using statistical tests to determine if there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis.
What are the types of tests?
There are various types of tests in statistics, including:
a. Hypothesis Tests: Used to make inferences about population parameters.
b. T-Tests: Assess differences between means of two groups.
c. Chi-Square Tests: Analyze the association between categorical variables.
d. ANOVA (Analysis of Variance): Compares means of multiple groups.
e. Regression Analysis: Examines relationships between variables.
f. Non-parametric Tests: Statistically analyze data when assumptions of parametric tests are not met.
What is a random variable?
A random variable is a variable in probability theory that can take on different values with certain probabilities. It represents the outcomes of a random process or experiment. Random variables can be discrete (with countable outcomes) or continuous (with an infinite number of possible values).
What is distribution?
In statistics, a distribution refers to the set of all possible values and their associated probabilities or frequencies for a random variable. It describes how the values of a random variable are spread or distributed. Common probability distributions include the normal distribution, binomial distribution, and Poisson distribution, each with specific characteristics and applications.
#statistics #statisticsfordatascience #statisticstutorials #scaler
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