**What is SSC CGL** statistics paper requires is regular practice of concepts and their application.

__SSC CGL 2020: Sampling Theory__

· Sampling is the statistical process of collecting data from small individual group

form within a large population to estimate the characteristic of whole

population.

· Sampling theory is the field of statistics which includes gathering, analysis and

interpretation of sample data gathered from a population.

· It uses concept of probability theory.

· Here samples are gathered on predefined parameters and a conclusion has been

drawn after analyzing that data.

**Process Of sampling**:

· Identify the population.

· Select the sample set.

· Define the basis of selection of sample set over the population.

· Check thoroughly whether sample set is reflecting all the attributes of

population or not.

· Check for the errors.

· Define the sample set.

**Types of sampling:**

· Random Sampling

· Systematic sampling

· Stratified sampling

__SSC CGL 2020: Analysis of Variance__

· Analysis of variance is an analytical tool in statistics that splits variability of a

data set into two parts named systematic factors and random factor.

· This test is applied in regression analysis.

· It identifies the influence of independent variable on dependent variable.

· This was developed by statistician Ronald Fisher.

· It works on mean value of population set.

· Analysis of variance tool is applied to analyze experimental data.

· It performs multiple sample comparisons.

** Formula for Analysis of variance (ANOVA):**

*ANOVA Coefficient *=

There are two types of analysis of variance possible and these are as follows:

1. **Unidirectional (one way) Method: It determines whether all the samples are same or**

** not.**

2. **Two way Method: It is an extension of unidirectional analysis of variance. **

** Here we analyze the impact of two independent variables over a dependent variable.**

__SSC CGL 2020: Time Series Analysis__

· Time series is a sequence defined at successive equally spaced points in time

space.

· It is a sequence of discrete time data.

· Time series are plotted via line charts.

· It is used in statistics, weather forecasting (height of ocean tides), earthquake

prediction, pattern recognition and signal processing.

**Time Series Analysis** is method for analyzing time series data to find meaningful information of data.

There are two methods available for time series analysis

1. **Time domain Method**

2. **Frequency domain method**

Time series pattern can be defined under following two basic components:

1. **Seasonality**

2. **Trend**

Identifying patterns of time series data is very important and there may be two types of pattern:

1. **Random Noise**

2. **Systematic pattern**

This analysis is based on assumption.

There are two basic goals of Time Series Analysis and theses are as follows:

· Identifying the nature of event by the sequence of observed dataset.

· Prediction of future values of variable on the basis of time series data.