statistics basics

1. SUBJECT:
Quantitative techniques
Topic: statistics
Presented by:
Shirisha R
Assistant professor
Regional college of management
Bangalore

2. Introduction to statistics:
 Statistics is a mathematical body of science that pertains to the collection,
analysis, interpretation or explanation, and presentation of data, or as a
branch of mathematics. Some consider statistics to be a distinct
mathematical science rather than a branch of mathematics. While many
scientific investigations make use of data, statistics is concerned with the
use of data in the context of uncertainty and decision making in the face of
uncertainty.
 In applying statistics to a problem, it is common practice to start with a
population or process to be studied. Populations can be diverse topics such
as "all people living in a country" or "every atom composing a crystal".
Ideally, statisticians compile data about the entire population (an operation
called census). This may be organized by governmental statistical institutes.
Descriptive statistics can be used to summarize the population data.
Numerical descriptors include mean and standard deviation for continuous
data (like income), while frequency and percentage are more useful in terms
of describing categorical data (like education).

3. When a census is not feasible, a chosen subset of the population called a
sample is studied. Once a sample that is representative of the population is
determined, data is collected for the sample members in an observational or
experimental setting. Again, descriptive statistics can be used to summarize
the sample data.
However, drawing the sample contains an element of randomness; hence, the
numerical descriptors from the sample are also prone to uncertainty. To draw
meaningful conclusions about the entire population, inferential statistics is
needed.
It uses patterns in the sample data to draw inferences about the population
represented while accounting for randomness. These inferences may take the
form of answering yes/no questions about the data (hypothesis testing),
estimating numerical characteristics of the data (estimation), describing
associations within the data (correlation), and modeling relationships within
the data (for example, using regression analysis).
Inference can extend to forecasting, prediction, and estimation of unobserved
values either in or associated with the population being studied. It can
include extrapolation and interpolation of time series or spatial data, and data
mining.

4. MEANING OF STATISTICS:
Statistical is a mathematical science pertaining to the collection, analysis,
interpretation or explanation, and presentation of data.
DEFINITION OF STATISTICS:
“statistics are numerical statements of facts in any department of enquiry,
placed in relation to each other”.
- Dr. A. L. Bowley
“statistics is the science of collection, presentation, analysis, and interpretation
of numerical data”.
-Croxton and Cowden

5. OBJECTIVES OF STATISTICS:
1. To draw conclusions about a population followed by an analysis of
information contained in sample data. This includes assessing the
degree of uncertainty in these inferences.
2. To plan the process and the observations can be used to draw valid
conclusions.
3. To determine the type and quantity of data that must be collected.
4. To analyse and draw conclusions from the data.
5. To assess the conclusions strengths and evaluate their uncertainty.

6. TYPES OF STATISTICS:
 Descriptive statistics:
descriptive statistics describe, show, and summarize the basic features of
a dataset found in a given study, presented in a summery that describes the
data sample and its measurements. It helps analysts to understand the data
better.
two main types of descriptive statistics:
1. Measures of central tendency
 Mean
 Median
 Mode
2. Measures of dispersion or variance
 variance
 Standard deviation
 Range

7. INFERENTIAL STATISTICS:
inferential statistics is a branch of statistics that makes the use of
various analytical tools to draw inferences about the population data
from sample data.
Two types of inferential statistics
1. Hypothesis testing
2. Regression analysis

8. Advantages of statistics:
1. Making sense of data
2. Identifying patterns and trends
3. Making predictions
4. Making decisions
5. Communicating information

9. Disadvantages of statistics:
1. Complexity
2. Bias
3. Limited scope
4. False sense of certainty
5. overreliance

10. Important terminologies of statistics:

11. THANK YOU