Introduction to Statistics
Thank you for showing interest in this course. We have organized this course in such a way that you get the basics as well as a taste of advanced topics on statistics.
We will also demonstrate few hands-on practical examples of statistics in action.
In addition, you will also learn the cross over of statistics and data science disciplines.
In case you have any questions, use ask the instructor option and we will respond as soon as we can.
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Meaning of Statistics
Meaning of Statistics
The word “Statistics” which comes from the Latin word status.
Furthermore word statistics refers to “Numerical Facts Systematically Arranged”. In this sense it is always used plural.
Statistics is defined as discipline that includes procedures & techniques used to collect, process & analyze numerical data to make inferences & to reach decisions under uncertainty.
It is the field of math that deals with the collection, tabulation and interpretation of numerical data.
An example of statistics is a report of numbers saying how many followers of each religion there are in a particular country.
Statistical Measures
Below are some of the common examples of statistical measures
- Sample mean, sample median, and sample mode.
- Sample variance and sample standard deviation.
- Sample quantiles besides the median, e.g., quartiles and percentiles.
- Test statistics, such as t-statistic, chi-squared statistic, f statistic.
- Order statistics, including sample maximum and minimum.
Use of Statistical Information
Statistics is applicable to a wide variety of academic disciplines, including natural and social sciences as well as government and business.
Some of the uses are:
- To inform general public
- To explain things that have happened
- To justify a claim
- To estimate the unknown quantities
Characteristics of Statistics
Statistics deals with those characteristics or aspects of things which can be described numerically either by counts or by measurements. Some of the characteristics are following:
- It consists of aggregates of facts. A single and isolated fact or figure like, 60 Kgs. weight of a student or the death of a particular person on a day is not statistics.
- It is effected by many causes. For example, result of class in a school does not depend on any single factor but collectively on standard of teachers, teaching methods, teaching aids, practical’s performance of students, standard of question papers and as well as of evaluation.
- It should be numerically expressed. For example, it should be expressed in quantitative form such as weights of 60, 70, 100 and 90 Kg. or profits of $100, $1,150.
- It must be enumerated or estimated accurately. For example, we can measure the height of a person precisely however when it comes to very large or tiny objects, we rely on estimating (guessing) how long or shot an object is.
- It should be collected in a systematic manner. The data collected in a haphazard manner will lead to difficulties in the process of analysis, and wrong conclusions. A good method is to use survey forms, online databases and specialized system to collect the data.
- It should be collected for a predetermined purpose or objectives such as what do we want to achieve out of this data collection. For example, while preparing population statistics, we need to know gender, city, date of birth, etc.
By the way, statistical laws are valid on the average or in the long run. There is no guarantee that a certain law will hold in all cases. Statistical inferences is therefore made in the face of uncertainty.
Importance of Statistics
Statistics is perhaps a subject that is used by everybody. Following are few functions and uses indicated:-
1) Statistics assists in summarizing the large sets of data in a form that is easily understandable.
2) Statistics assists in a sound and effective planning in any field of inquiry.
3) A businessman, an industrialist and a research worker all employ statistical methods in their daily work.
4) Bank, Insurance companies and Governments all have their statistics departments to assist them in creating statistical information as per their needs.
Statistical Terms
Descriptive Statistics: Deals with concepts and methods concerned with summarization and description of the important aspects of numerical data.
Example: A cricket player wants to find his scores average for the last 20 games.
Inferential Statistics: Deals with procedures for making inferences about characteristics that describe large group or date means population using part of data as sample.
Example: A cricket player wants to estimate his chance of scoring based on his current season average.
Population: It is a collection or set of all possible observations whether finite or infinite.
Sample: It is a part or a subset of a population.