Applied Statistics: Real World Problem Solving is a comprehensive course designed to equip you with the statistical tools and techniques needed to analyze real-world data and make informed decisions. Whether you’re a business analyst, data scientist, or simply looking to enhance your data analysis skills, this course will provide you with a solid foundation in applied statistics.
Introduction to Business Statistics: Understand the basics of data types and their relevance in business, along with the differences between quantitative and qualitative data.
Measures of Central Tendency: Learn about mean, median, and mode, and their importance in summarizing data.
Measures of Dispersion: Explore standard deviation, mean deviation, and quantile deviation to understand data variability.
Distributions and the Central Limit Theorem: Dive into different types of distributions and grasp the central limit theorem’s significance.
Sampling and Z-Scores: Understand the concepts of sampling from a uniform distribution and calculating Z-scores.
Hypothesis Testing: Learn about p-values, hypothesis testing, t-tests, confidence intervals, and ANOVA.
Correlation: Study the Pearson correlation coefficient and its advantages and challenges.
Advanced Statistical Concepts: Differentiate between correlation and causation, and perform in-depth hypothesis testing.
Data Cleaning and Preprocessing: Master techniques for cleaning and preprocessing data, along with plotting histograms and detecting outliers.
Statistical Analysis and Visualization: Summarize data with summary statistics, visualize relationships between variables using pair plots, and handle high correlations using heat maps.
By the end of this course, you will be equipped with the skills and knowledge to tackle real-world data problems using applied statistics. Enroll now and take the first step towards becoming proficient in statistical analysis!
