From f47a4c5220022798268921ff777af2d24dfb90a5 Mon Sep 17 00:00:00 2001 From: hemant087 <88886834+hemant087@users.noreply.github.com> Date: Tue, 25 Oct 2022 22:05:14 +0530 Subject: [PATCH] Revert "basic of statistic for data science" --- blogs/Statistics For Data Science.md | 60 ---------------------------- 1 file changed, 60 deletions(-) delete mode 100644 blogs/Statistics For Data Science.md diff --git a/blogs/Statistics For Data Science.md b/blogs/Statistics For Data Science.md deleted file mode 100644 index 06ade10..0000000 --- a/blogs/Statistics For Data Science.md +++ /dev/null @@ -1,60 +0,0 @@ -

Why Should I Learn Statistics?

- -Variation is an inevitability facet of life! Every process has variation.High variation means low quality. -**Decision makers make better decisions when they use all available information in an effective and -meaningful way. The primary role of statistics is to provide decision makers with methods for obtaining and -analyzing information to help make these decisions. Statistics is used to answer long-range planning -questions, such as when and where to locate facilities to handle future sales.** - - -**Just like weather, if we cannot control something, We should learn how to measure and analyze in -order to predict it, effectively.** - -``The aim of this blog is to provide you with hands-on -experience to promote the use of statistical thinking and techniques to apply them to make educated decisions -whenever you encounter variation in business data.`` - -

What Is Business Statistics?

- -The main objective of Business Statistics is to make inferences (predictions, decisions) about certain -characteristics of a population based on information contained in a random sample. - -Business Statistics is the science of "good" decision making in the face of uncertainty and is used in many -disciplines, such as financial analysis, econometrics, auditing, production and operations, and marketing -research. It provides knowledge and skills to interpret and use statistical techniques in a variety of business -applications. -- Carefully planned statistical studies remove hindrances to high quality and productivity at every stage of -production, saving time and money. It is well recognized that quality must be engineered into products as -early as possible in the design process. One must know how to use carefully planned, cost-effective -experiments to improve, optimize and make robust products/services and processes data. - -Statistical topics are about decision-making with respect to the characteristics of a group of persons or objects -on the basis of numerical information obtained from a randomly selected sample of the group. - -

Types of Statistical Analyses:

- -- ``Descriptive Statistics`` is concerned with summary calculations, graphs, charts, and tables. - -- ``Inferential Statistics`` is a method used to generalize from a sample to a population. For example, the -average income of all families in the US (the population) can be estimated from figures obtained from a -few hundred families (the sample). - - -

Statistical Population:

A statistical population is the collection of all possible observations with a specified -characteristic of interest. -**An example :** all the students in the College is population then ECE, Computer Science ,1st year,2nd Year and etc, are the sample. Note -that a sample is a subset of the population. -

Variable:

A variable is an item of interest that can take on many different values. - -

Types of Variables or Data:

- -- ``Qualitative Variables`` are non-numerical variables that cannot be measured. Examples include gender, -religious affiliation, place of birth. - -- ``Quantitative Variables`` are numerical variables that can be measured. Examples include balance in -your checking account, number of children in your larger family. Note that quantitative variables are -either discrete (which can assume only certain values, and there are usually "gaps" between the values, -such as the number of bedrooms in your house) or continuous (which can assume any value within a -specific range, such as the air pressure in a tire). - -