.IntroductionAssessment Title:Data Management The aim of this unit is to provide students with an understanding of how management information and decision-making are enhanced by the application of...

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Answer To: .IntroductionAssessment Title:Data Management The aim of this unit is to provide students with an...

Payal answered on Jul 01 2021
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Statistics for Management
TABLE OF CONTENTS:
1. PURPOSE
2. TASK 1 DATA ANALYSIS & REPORTING
2.1 LO1 & 2
2.1.1 Evaluate the nature and process of business and economic data/information from a range of different published sources
2.1.2 Evaluate data from a variety of sources using different methods of analysis
2.1.3 Analyse and evaluate qualitative and quantitative raw business data from a range of examples using appropriate statistical methods
3. TASK 2 DATA INSIGHTS
3.1 LO3 & 4
3.1.1 Apply a range of statistical methods used in business planning for quality, inventory and capacity management
3.1.2 Using appropriate charts/tables communicate findings for a number of given variables
1. PURPOSE:
The o
bjective of this activity is to develop an understanding the importance of Management Information System (MIS) in Decision Making though various Statistical Techniques. There is a well-known saying “Data acts as an oil in the 21st Century”. This data is available in various forms (e.g. raw form, semi-finished, sorted, etc.) over various platforms & can be accessed by any individual at any given point of time. The criticality lies in the fact that how this data should be read, analysed, visualized so that sensible output can be drawn for decision making.
There process of turning raw data into useful information by applying various advanced analytical & statistical techniques to gain better insights about the business operations is known as Data Analysis. These business insight brings the hidden opportunities of overall operations onto the surface for better decision making. During the past few years, it has emerged as one of the key activity for the smooth running of any business organisation.
In this report we will be looking at various aspects of Data collection, Data mining and Data interpretation in order to help in making meaningful business decisions. (Anderson, 2010)
2. TASK 1 DATA ANALYSIS & REPORTING:
2.1 LO1 & 2:
2.1.1 Evaluate the nature and process of business and economic data/information from a range of different published sources.
Introduction to Statistics:
Statistics is an information which is expressed in numerical terms. The numerical information could be related to Business, Economy, population, healthcare, etc. The nature & the specific fields define the domain of which the data is related to which are further analysed through various relevant techniques to draw insights out of it. For e.g. we can apply what if analysis, customer segmentation and cohort analysis to the business data. These all aspects are concerned with the process of the data.
Characteristics of Statistical data
According to Horace Secrist, there are seven characteristics of statistics
1) Data should be based of aggregation of Facts
2) Effect of all variables should be considered
3) Numerical expression
4) Accuracy
5) Sorted & Systematic
6) Data should consist the parameters which defines the purpose
7) Relation between all variables
Benefits of Statistical data:
As discussed in the beginning, data is an Oil in the 21st century. The businesses are giving more importance their data and their competitor’s data for proper comparison of the business position, in order to make better strategic decisions for the businesses. The benefits of statistical data can be gauged from the fact that the Uber, Ola are managing their whole businesses operations solely on the customer’s past data available in the database. (Morris, 2012)
Components of Statistics:
1) Domain of Data – It involves collecting the data for which the analysis needs to be done.
2) Population – It in involves considering the all factors of interest into account
3) Variable – This involves analysing the variables that are present in the data- numerical, character, ordinal.
4) Sample- It involves taking the part of the data, which fairly represent each dimension, in order to meaningful analysis.
Numerical scale of measurement
The numerical scale of any data helps in measuring the variable in a much better and accurate way, in order to derive concrete conclusions out of it.
Nominal- Nominal data involves assigning the numerical value to any variable. For e.g. 1 for Male and 2 for Female or for that matter the diabetic can be indicated by 1 and non-diabetic patients can be denoted by 2.
Ordinal – The data which is denoted by rank is known as ordinal data. For e.g. assigning 1st, 2nd and 3rd rank. Or for e.g. the level of severity in patient can be ranked by assigning 1, 2, 3-meaning 1 high severity and 3 – Normal patient.
Interval - Interval data type is the one which is measured along the numeric scale and each point is at the equal distance from one another. For example, Celsius Temperature is a classic example of interval data as the difference between the 10 degree Celsius and 20 degree Celsius is the same as for 20 and 30 degree Celsius.
Ratio - Ratio are almost similar to intervals with the exception that ratios cannot be in negative, whereas interval can be both positive and negative. Ratio data type gives good picture of the data. For e.g. for knowing the profit per unit of output sold, we can use the ratio for knowing the per unit profit
2.1.2 Evaluate data from a variety of sources using different methods of analysis
Sources:
The data which is to be used for the analysis can be obtained from two sources-
1) Primary Data Source- In this the data is collected by the researcher themselves through various means like- interview, questionnaire, and etc. but it takes a lot of time and efforts to collect the data via primary data source.
2) Secondary Data Source – In this data is collected by someone else, and it is simply used by the researcher for his analysis. It can reduce the time and effort required in collecting the data. These kinds of data can be obtained from different websites like data, world and etc.
Methods of Analysis:
The data that has been obtained from different sources can be analysed by using two approaches.
1) Deductive - In this approach the existing data is analysed based on the past events. The events which have occurred in the past help us to draw conclusion out of the data.
2) Inductive – In this approach new facts and knowledge is drawn from the existing data. This is done by Hypothesis testing and various advanced statistical test available. A particular statement or theory is tested and observation are drawn from testing the fact on the new data and finally theory or a particular fact is confirmed.
There are also four other types of analytical methods for analysing the particular data –
1) Descriptive Analysis
2) Exploratory Analysis
3) Confirmatory Analysis
4) Inferential Analysis
1) Descriptive Analysis is concerned with the description of the data. It helps us to tell the situation of past. There are various statistical techniques which can be used for descriptive analysis. These are categorized into four type as below -
· Measures of Frequency
· Measures of Central Tendency
· Measure of Dispersion or Variation
· Measure of Position
a) Measures of Frequency- It measures the number of times the particular event has occurred. The frequency is handy tool for analysing the transaction data. For example the business case where we want to analyse how many time customers have ordered the particular product can help us study the...
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