Lecture 1.1 - Introduction and Types of Data - Basic definitions

Question 1

Learning objectives

Answer 1

1. Statistics involves analyzing data through descriptive and inferential statistics and distinguishing between a sample and a population.
2. Data collection involves identifying variables and observations in a dataset.
3. Types of data include categorical and numerical data, cross-sectional and time-series data, and different measurement scales.
4. Working with data includes creating, downloading, manipulating, and analyzing subsets of data.
5. Framing questions that can be answered with data is a crucial step in statistical analysis.

Question 2

What is Statistics?

Answer 2

Statistics is the art of learning from data. It is concerned with the collection of data, their subsequent description, and their analysis, which often leads to the drawing of conclusions.

Question 3

Major branches of statistics

Answer 3

1. Descriptive statistics describes and summarizes data.
2. Inferential statistics draws conclusions from data, taking into account chance.

Question 4

Population and sample

Examples Only

Answer 4

1. Percentage of Indian students who passed 12th grade and study engineering.
2. Prices of houses in Tamil Nadu.
3. Total sales of cars in India in 2019.
4. Age distribution of visitors to a city mall in a particular month.

Question 5

Population and sample

Definition

Answer 5

1. Population: Total collection of elements of interest.
2. Sample: Subgroup of the population studied in detail.

Question 6

Purpose of statistical analysis

Answer 6

1. Descriptive study: Examines information for intrinsic interest.
2. Inferential study: Uses information from a sample to draw conclusions about the population.
3. Descriptive study can be performed on a sample or population.
4. Study becomes inferential when an inference is made about the population based on information obtained from a sample.