Statistics for Management

This presentation provides an overview of statistics for management. It covers the key characteristics of statistics, the different methods used in statistics (descriptive and inferential), types of data sources, the difference between sample and population, the value of employing statistical methods, analyzing sample data, and a conclusion. It also includes financial information of Apple, MSFT, Amazon, and Netflix companies.

Statistics for Management
Part 1
Part 2

Key characteristics of statistics
• It includes the aggregate facts
• Data can be effected due to many cause
• Data should be expressed in numerical form
• Information should be collected in a systematic manner

Overview of statistical methods
• Descriptive Statistics: It is deal with the help presentation or collection of data
where initially statistical data should be analyse which is not so simple.
• Inferential Statistics: This statistical method used to draw right conclusion with
the help of statistical analysis that used descriptive statistics.

Type of data source and information
• Print information: It include the vast area such as newspaper, books, microfiche
etc. federal government report also include in the print sources of data which
organizations can access.
• Online information: In the current scenario of business environment, all the data
or information can easily available on online platform which help the
organization to access and used in the strategic development process.

Difference between sample or population
Sample Population
Sample includes a subset or a part of a population.
Size of sample always less than a size of population. It include all the set of specified group which comes
under the population such as all people living in the
UK.
Sample measurement characteristics called statistics
(Keller, 2015). Measurement characteristics of population such as
mean or standard deviation called parameter.

Evaluation the value of employing
statistical method
• With the help of statistics organization able to evaluate various
measurements which further helps in strategic decisions.
• Statistics use numerical evidence in order to draw the valid or accurate
conclusion.
• Statisticians know that how to implement data in effective manner in
order to avoid difficulty.

Difference between descriptive or
inferential statistics
Descriptive Statistics Inferential Statistics
It is used when entire population data is available.
So in this case, sample size not required. It is used when size of population is too large, so
that time representative sample is required.
Descriptive data is limited because it is applied
only on actually measured information. Whole population data can be analysed with the
help of sample parameters.
Properties of descriptive statistics are mean,
median, mode etc. which is also called parameters. Properties of inferential statistics will be know as
statistics only not parameters.
Descriptive data is 100% accurate because there are
no assumptions made during the analysis. This statistics are not 100% accurate because large
population based on small samples which can vary
the results.

Analyzing the given sample set of data
• Mean: It is the sum of numbers which given in the list of items which help in
analysing the overall trend.
• Standard deviation: This analysis used to calculate the data which spread
around all over the mean. It is more useful for quick determination dispersion of
data point.
• Regression: This analysis is based on the relationship between dependent or
explanatory variables which plotted on charted on a scatter plot.

Financial Information

Apple Company

MSFT Company

Amazon Company

Netflix Company

Conclusion
• From the given presentation it has been concluded that, statistical is very
important for every organization in order to analyse data and build effective
strategic decisions.
• Descriptive and inferential statistics used to evaluate data but it will be apply
according to the size of population. Statistics methods help the managers to
develop strategy and make sure to implement in effective manner which further
beneficial in meeting business objectives and goals.

REFERENCES
Embrechts, P. and Hofert, M., 2014. Statistics and quantitative risk management for
banking and insurance. Annual Review of Statistics and Its Application. 1.
pp.493-514.
Keller, G., 2015. Statistics for Management and Economics, Abbreviated. Cengage
Learning.

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