Week 1 DQ1 – Data Analysis and Business Intelligence | Westcliff University

Note : Only For Reference

In the first week of our course, we dealt with the basic concepts of Statistics which included its use in our daily life and business, types of statistics, types of variables, and different levels of measurement (nominal, ordinal, interval and ratio).We also discussed practice of statistics should be guided by ethical behavior.

Usefulness of Statistical Knowledge in Business

Statistics is the practice or science of collecting and analyzing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample (Statistics).

Knowledge of Statistics is important in business because the various statistical techniques can be used by business organizations in their areas of operation (marketing, finance, production, research, manpower planning) for making sales projections, financial analysis of capital expenditure projects, constructing profit projections for a new product, setting up production quantities, and making a sampling analysis to determine the quality of a product.

Difference between Descriptive and Inferential Statistics

 

S. No.

Descriptive Statistics

Inferential Statistics

1.

Descriptive Statistics gives description or we can say it focuses on collection, presentation and characterization about a sample.

Inferential Statistics helps to predict and estimate the possible characteristics of the population from the sample data drawn from the population.

2.

Drawing conclusion in descriptive statistics is limited within the given data i.e. we cannot make conclusions beyond the given data.

Drawing conclusion in Inferential statistics is unlimited i.e. the educated predictions and guesses can be made on the basis of the parameters of the given population.

3.

Example:

·         Frequency of the variables.

·         Population of the particular country.

 

Example:

·         Grades or percentile of the scores.

·         Average score in cricket.

 

Qualitative Variables and Quantitative Variables

Variables

Definition

Examples

 

 

Qualitative Variables

Qualitative variables are those variables that are non-numerical or can’t be measured or can’t be quantified. 

 

·         Gender

·         Religion

·         Hair color, etc.

 

Quantitative Variables

Quantitative variables are those variables that can be measured on a numeric or quantitative scale. 

 

·         Height

·         Weight

·         Age, etc.

 

Discrete Variables and Continuous Variables

Variables

Definition

Examples

 

 

Discrete Variables


A discrete variable is a variable whose value is obtained by counting.

 

·         number of students present

·         number of red marbles in a jar

 

 

Continuous Variables

A continuous variable is a variable whose value is obtained by measuring.

 

·         height of students in class

·         weight of students in class

 

 

 

Difference between different Data levels of Measurement

Data Levels of Measurement

Definition

Examples

 

 

 

 

Nominal Level

In this level of measurement, the numbers in the variable are used only to classify the data. 

·         Gender

·         Religion

·         Eye Color

 

 

Interval Level

In this level of measurement, the variables are still classified into ordered categories, but there is an equivalent distance between these categories. 

·         Shoe size

·         Temperature Scale

 

Ordinal Level

In this level of measurement, data arranged in some order, but the differences between data values cannot be determined or are meaningless.

Ranking of soft drinks

1.      Coke

2.      Sprite

3.      Fanta

 

Ratio Level

In this level of measurement, the observations, in addition to having equal intervals, can have a value of zero as well. 

·         Height

·         Weight

·         Duration

 

Classification of Different Variables

Variables

Categories

1.      Salary

Ratio

2.      Gender

Nominal

3.      Sales Volume of MP3 players

Ratio

4.      Soft drink preference

Ordinal

5.      Temperature

Interval

6.      SAT Scores

Interval

7.      Student rank in Class

Ordinal

8.      Rating of a finance professor

Ordinal

9.      Number of a home video screen

Ratio

 

 

 

References

 

Statistics. (n.d.). Retrieved from English Oxford Living Dictionaries: https://en.oxforddictionaries.com/definition/statistics

 

 

Author: Smirti

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