Statistics is the science of collecting, organizing, analysing, interpreting, and presenting data. It plays a crucial role in various fields such as business, economics, medicine, psychology, sociology, and more. With the increasing availability of data in today’s digital age, the ability to interpret and make sense of data has become more important than ever.
In this book, we will explore key topics in basic statistics, covering various methods for summarizing data, understanding probability distributions, analysing relationships between variables, and conducting hypothesis testing. The content is structured into three main sections: Data Summarization, Parametric Statistics, and Non-parametric Statistics.
The first section, Data Summarization, lays the foundation by introducing techniques for summarizing and describing data. We will explore measures of frequency, percentage, percentile, central tendency, and variability, which are essential for understanding the characteristics of a dataset.
Moving forward, we delve into the realm of probability distributions, focusing on the Normal Probability Curve and its characteristics, as well as concepts like skewness and kurtosis, which help us understand the shape of distributions.
The second section, Parametric Statistics, explores techniques for analyzing data under specific assumptions about the population distribution. We will cover topics such as mean differences, correlation and regression analysis, which are commonly used in inferential statistics to make predictions and draw conclusions about populations based on sample data.
Finally, the third section, Non-parametric Statistics, offers alternative methods for analyzing data when the assumptions of parametric statistics are not met. We will explore techniques such as the Chi-square test, rank-order correlation, and various non-parametric tests for comparing groups.
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