Course Content

UNIT 1:Analyzing data in categories

Techniques for handling categorical data are covered in this unit. Discover how to identify patterns and correlations in category data by using bar graphs, Venn diagrams, and two-way tables.

UNIT 2: Quantitative Data Exploration

Some fundamental techniques for graphing quantitative data distributions, such as stem and leaf plots, histograms, and dot plots, are covered in this subject. We'll also look at how to compare the features of other distributions using those displays.

UNIT 3: Quantitative Data Summary

Common center measurements like mean and median are included in this unit. Additionally, we will study how to quantify variability and spread using the standard deviation and interquartile range, and we will apply these concepts to identify data that may be classified as outliers.

UNIT 4: Quantitative Data Analysis: Percentiles & Z-Scores

We'll learn how to model distributions with density curves, how to assess the position of data within a distribution using percentiles and z-scores, what happens when we transform data, and an examination of one of the most significant families of distributions: the normal distributions.

UNIT 5: Bi-Variate Quantitative Analysis

The link between two quantitative variables is investigated using scatter plots, and the relationship is modelled and predictions are made using regression. This section looks at linear regression and how to evaluate a linear model's strength.

UNIT 6: Collecting data

Forming questions and acquiring data to investigate them are the fundamental components of statistics. This section links these inquiries to elements of research design, such as fundamental experiment design, observational studies, and sample and survey techniques.

UNIT 7: Probability

Here, we'll delve deeply into the various methods available for determining the probability of certain occurrences. We'll lay a strong foundation by applying simulations and the addition and multiplication rules, which will enable us to solve statistical problems in the future.

UNIT 8: Random variables and probability distributions

in this unit we will determine the expected value and probability of each random variable, as well as how to combine and transform them.

UNIT 9: Sampling distributions

A sampling distribution helps us utilize samples to estimate the probability. The behavior of sample means and proportions in repeated samples is covered in this unit.

UNIT 10: Quantitative Mean Inference

This section will provide you with the tools to construct an inference from a population mean to make predictions about quantitative outcomes, ranging from quality control to forecasting the amount of snowfall that would result from an impending storm.

Statistics is the backbone of informed decision-making, from business analytics to scientific research.Our instructors are seasoned statisticians with a passion for demystifying data analysis.We bring statistics to life through interactive lessons, real-world case studies, and practical applications.

Join us on this statistical journey and unlock the power of data analysis.