Statistics Data

Introduction

• Every experiment starts with Data Collection, followed by Data Analysis.
• Data Collection can be from any source.
• Data Analysis is the process of applying logical or statistical techniques to evaluate and describe data in a meaningful way.

Categories

Two broad categories of statistics that help in data analysis are:

• Descriptive Statistics
• Inferential Statistics

Descriptive Statistics

Descriptive Statistics:

• Provides summary statistics of data.
• Helps to quantitatively interpret the features of data.

Descriptive Statistics - Measures

Measures of Central Tendency

Focus on the average or central point of a dataset.

• Mean
• Median
• Mode

Measures of Spread

Focus on the dispersion of data from the central point.

• Range
• Standard Deviation
• Variance
• Interquartile Range

Inferential Statistics

• Makes inferences about the properties of a population.
• Makes propositions about a population.

Inferential Statistics - Terms

Estimation

Process of analyzing the parameter of population.

Point Estimation

Single value that determines the parameter of population.

Confidence Intervals

Range of values within which the parameter is included.

Hypothesis Tests

Specific values of the parameter are tested.

Inferential Statistics - Measures

Estimation

In this process, a sample is drawn from a population to estimate the following:

• Parameter: Mean, Standard Deviation, Proportion, Correlation.

• Confidence Interval: Range of values of an unknown population parameter.

Hypothesis Testing

A hypothesis test helps in determining whether to reject or retain a claim about a population, depending on the evidence provided by a sample of data.

Descriptive vs Inferential