Management Notes

# Management Notes

Reference Notes for Management

# 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.

The 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