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Statistics for Data Science

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Overview

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Dive into a comprehensive 10-hour statistics course designed for data science applications. Explore essential statistical concepts through real-life lecture formats, working through various examples to gain a deep understanding of standard deviation, normal distribution, bivariate analysis, and more. Focus on grasping underlying concepts rather than memorizing formulas and calculations. Cover topics including sampling distributions, hypothesis testing, confidence intervals, t-tests, ANOVA, chi-square tests, and linear regression. Learn how to apply statistical methods in data science contexts, with additional resources available for implementing concepts using R programming. Enhance your statistical knowledge with practical examples, clear explanations, and a focus on real-world applications in data science.

Syllabus

Statistics Course Overview | Best Statistics Course | MarinStatsLectures.
Statistics Video Tutorials at a Glance | Best Statistics Tutorials | MarinStatsLectures.
Statistics Terminology and Definitions| Statistics Tutorial | MarinStatsLectures.
Study Designs (Cross-sectional, Case-control, Cohort) | Statistics Tutorial | MarinStatsLectures.
Variables and Types of Variables | Statistics Tutorial | MarinStatsLectures.
Bar Chart, Pie Chart, Frequency Tables | Statistics Tutorial | MarinStatsLectures.
Histograms and Density Plots for Numeric Variables | Statistics Tutorial | MarinStatsLectures.
Boxplots in Statistics | Statistics Tutorial | MarinStatsLectures.
Plots for Two Variables | Statistics Tutorial | MarinStatsLectures.
Describing Distributions: Center, Spread & Shape | Statistics Tutorial | MarinStatsLectures.
Mean, Median and Mode in Statistics | Statistics Tutorial | MarinStatsLectures.
Percentiles, Quantiles and Quartiles in Statistics | Statistics Tutorial | MarinStatsLectures.
Measures of Spread & Variability: Range, Variance, SD, etc| Statistics Tutorial | MarinStatsLectures.
Standard Deviation & Degrees of Freedom Explained | Statistics Tutorial | MarinStatsLectures.
Sample and Population in Statistics | Statistics Tutorial | MarinStatsLectures.
Normal Distribution, Z-Scores & Empirical Rule | Statistics Tutorial #3 | MarinStatsLectures.
Samples from a Normal Distribution | Statistics Tutorial #4 | MarinStatsLectures.
Central Limit Theorem & Sampling Distribution Concepts | Statistics Tutorial | MarinStatsLectures.
Standard Error of the Mean: Concept and Formula | Statistics Tutorial #6 | MarinStatsLectures.
Confidence Interval Concept Explained | Statistics Tutorial #7 | MarinStatsLectures.
Hypothesis Testing Explained | Statistics Tutorial | MarinStatsLectures.
t-distribution in Statistics and Probability | Statistics Tutorial #9 | MarinStatsLectures.
Confidence Interval for Mean with Example | Statistics Tutorial #10 | MarinStatsLectures.
Margin of Error & Sample Size for Confidence Interval | Statistics Tutorial #11| MarinStatsLectures.
Bootstrapping and Resampling in Statistics with Example| Statistics Tutorial #12 |MarinStatsLectures.
Hypothesis Testing: Calculations and Interpretations| Statistics Tutorial #13 | MarinStatsLectures.
Hypothesis Testing: One Sided vs Two Sided Alternative | Statistics Tutorial #14 |MarinStatsLectures.
Hypothesis Test vs. Confidence Interval | Statistics Tutorial #15 | MarinStatsLectures.
Errors and Power in Hypothesis Testing | Statistics Tutorial #16 | MarinStatsLectures.
Power Calculations in Hypothesis Testing | Statistics Tutorial #17 | MarinStatsLectures.
Statistical Inference Definition with Example | Statistics Tutorial #18 | MarinStatsLectures.
Bivariate Analysis Meaning | Statistics Tutorial #19 | MarinStatsLectures.
Bivariate Analysis for Categorical & Numerical | Statistics Tutorial #20 | MarinStatsLectures.
Paired t Test | Statistics Tutorial #21| MarinStatsLectures.
Wilcoxon Signed Rank Test | Statistics Tutorial #22 | MarinStatsLectures.
Two Sample t-test for Independent Groups | Statistics Tutorial #23| MarinStatsLectures.
Two Sample t-Test:Equal vs Unequal Variance Assumption| Statistics Tutorial #24| MarinStatsLectures.
Bootstrap Hypothesis Testing in Statistics with Example |Statistics Tutorial #35 |MarinStatsLectures.
Bootstrap Confidence Interval with Examples | Statistics Tutorial #36 | MarinStatsLectures.
Permutation Hypothesis Testing with Example | Statistics Tutorial # 37 | MarinStatsLectures.
One Way ANOVA (Analysis of Variance): Introduction | Statistics Tutorial #25 | MarinStatsLectures.
ANOVA (Analysis of Variance) and Sum of Squares | Statistics Tutorial #26 | MarinStatsLectures.
ANOVA Part III: F Statistic and P Value | Statistics Tutorial #27 | MarinStatsLectures.
ANOVA Part IV: Bonferroni Correction | Statistics Tutorial #28 | MarinStatsLectures.
Chi Square Test of Independence | Statistics Tutorial #29| MarinStatsLectures.
Odds Ratio, Relative Risk, Risk Difference | Statistics Tutorial #30| MarinStatsLectures.
Case-Control Study and Odds Ratio | Statistics Tutorial #31| MarinStatsLectures.
Simple Linear Regression Concept | Statistics Tutorial #32 | MarinStatsLectures.
Linearity and Nonlinearity in Linear Regression | Statistics Tutorial #33 | MarinStatsLectures.
R Squared or Coefficient of Determination | Statistics Tutorial | MarinStatsLectures.

Taught by

MarinStatsLectures-R Programming & Statistics

Reviews

5.0 rating, based on 1 Class Central review

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  • Profile image for Manal Ibham
    Manal Ibham
    The lessons were details and very useful. I was able to follow and learn a lot about Statistics for data which will help.me.professionally.

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