Statistics for Data Science & Business Analytics in Python

Statistics for Data Science & Business Analytics in Python, available at $49.99, has an average rating of 4.67, with 76 lectures, 19 quizzes, based on 9 reviews, and has 61 subscribers.

You will learn about Foundational understanding of python to analyze data using NumPy and Pandas, and use statistical packages such as SciPy and statsmodels. Analyzing and visualizing data using python using line charts, bar charts, pie charts, histogram and box plots. Conducting univariate and bivariate analysis using one-way tables, two-way tables. Descriptive statistics for univariate and bivariate analysis – mean, median, mode, range, IQR, variance, standard deviation, covariance and correlation. Data distributions, including mean, variance, and standard deviation, T-distribution and normal distributions and z-scores. Probability, including union vs. intersection and independent and dependent events and Bayes' theorem. Sampling distribution, central limit theorem and intuition behind using central limit theorem in hypothesis testing. Hypothesis testing, including inferential statistics, significance level, type I and II errors, test statistics, and p-values. Test of proportions and chi-squar Simple Linear Regression using manual method as well as using OLS package in python, Multiple Linear regression, and predicting using the regression model. This course is ideal for individuals who are Anyone who wants to build a career in data science but lacks the foundational skills in statistics or Data analysts who are familiar with analyzing data but want to learn concepts in statistics to be able to do rigorous analysis or Masters and research students who would like to learn statistics or Data analysts who are familiar with data analysis in excel but want to learn statistics using python or Data visualization experts who would like to explore statistics using python It is particularly useful for Anyone who wants to build a career in data science but lacks the foundational skills in statistics or Data analysts who are familiar with analyzing data but want to learn concepts in statistics to be able to do rigorous analysis or Masters and research students who would like to learn statistics or Data analysts who are familiar with data analysis in excel but want to learn statistics using python or Data visualization experts who would like to explore statistics using python.

Enroll now: Statistics for Data Science & Business Analytics in Python

Summary

Title: Statistics for Data Science & Business Analytics in Python

Price: $49.99

Average Rating: 4.67

Number of Lectures: 76

Number of Quizzes: 19

Number of Published Lectures: 76

Number of Published Quizzes: 19

Number of Curriculum Items: 95

Number of Published Curriculum Objects: 95

Original Price: $129.99

Quality Status: approved

Status: Live

What You Will Learn

• Foundational understanding of python to analyze data using NumPy and Pandas, and use statistical packages such as SciPy and statsmodels.
• Analyzing and visualizing data using python using line charts, bar charts, pie charts, histogram and box plots.
• Conducting univariate and bivariate analysis using one-way tables, two-way tables.
• Descriptive statistics for univariate and bivariate analysis – mean, median, mode, range, IQR, variance, standard deviation, covariance and correlation.
• Data distributions, including mean, variance, and standard deviation, T-distribution and normal distributions and z-scores.
• Probability, including union vs. intersection and independent and dependent events and Bayes' theorem.
• Sampling distribution, central limit theorem and intuition behind using central limit theorem in hypothesis testing.
• Hypothesis testing, including inferential statistics, significance level, type I and II errors, test statistics, and p-values. Test of proportions and chi-squar
• Simple Linear Regression using manual method as well as using OLS package in python, Multiple Linear regression, and predicting using the regression model.

Who Should Attend

• Anyone who wants to build a career in data science but lacks the foundational skills in statistics
• Data analysts who are familiar with analyzing data but want to learn concepts in statistics to be able to do rigorous analysis
• Masters and research students who would like to learn statistics
• Data analysts who are familiar with data analysis in excel but want to learn statistics using python
• Data visualization experts who would like to explore statistics using python

Target Audiences

• Anyone who wants to build a career in data science but lacks the foundational skills in statistics
• Data analysts who are familiar with analyzing data but want to learn concepts in statistics to be able to do rigorous analysis
• Masters and research students who would like to learn statistics
• Data analysts who are familiar with data analysis in excel but want to learn statistics using python
• Data visualization experts who would like to explore statistics using python