In this session, you were introduced to the concepts of statistics and basics of data visualisation.
Data, today, is one of the most important tools that, if read properly, can reveal many doors and solutions at
the same time. In this session, you learnt the basics of statistics and how to use data visualisation effectively.
First, you learnt what statistics is and the basic concepts in statistics.
Statistics is basically collection, summarisation, analysis and reporting of data in a well-organised manner.
There are two types of statistics:
1. Descriptive statistics: In this type of statistics, you analyse the data that has been collected and find
patterns in them. It is often used to analyse past performances of the employees or marketing tactics.
2. Inferential statistics: In this type of statistics, you analyse the data and predict future events. For
instance, predicting company sales and impact of marketing strategy.
Next, you explored the basic concepts in statistics, which included:
1. Data: Any information collected or generated from online activity or otherwise is known as data. Any
attribute of an object can be recorded as data. For example, the most bought dress, the cost of a dress,
etc.
2. Dataset: A collection of data for a particular study is known as a dataset. For example, various types of
purchases made on christmas.
3. Variable: Any characteristics such as age, weight etc that can be measured or counted. Suppose you
need to use some data repeatedly in a report. Here, you can define a variable, that is, a name that
represents the data. You can then use the variable instead of describing the whole data repeatedly in a
report.
Types of variables:
● Qualitative or categorical variables
● Quantitative variables
○ Discrete variables
○ Continuous variables
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Data visualisation is a part of statistics that helps you build a narrative and present your data in the best
possible way.
First, you learnt bar graphs as a data visualisation tool.
You learnt that bar graphs show relative data of various components of data.
Given below is an example of a data represented in the form of bar graph:
Next, you learnt how to create a bar chart in Excel:
1. Select the range. For example, F1:G16.
2. In the Insert tab, of the Charts group, click on the Column symbol.
3. Select the desired type of bar graph.
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4. The resultant bar graph will appear on your sheet.
Next, you learnt another data visualisation tool, that is, pie charts.
Pie chart is the circular representation of data. A pie chart is used when 100% of data needs to be represented
and the division of categories is within 100%.
Given below is an example of a data represented in the form of pie charts:
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Next, you learnt how to make pie charts in Excel.
1. Select a range, say, A1:D2.
2. In the Insert option, select the Pie symbol.
3. Select the desired type of pie chart.
4. The final result will appear on the Excel sheet. Add labels as necessary.
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Next, you learnt another visualisation tool, that is, histograms.
A histogram is a visual representation of the distribution of data. The data can be of two types, numerical and
categorical. Two important points about histograms are as follows:
● A histogram is an extended form of a bar graph in which there are no gaps between adjacent bars.
● To construct a histogram, you need to first construct a frequency distribution table.
Finally, you learnt how to make a histogram in Excel.
1. Enter the bin numbers (upper levels) in the desired range (say, C8:C15).
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2. Click on Data Analysis in the Data tab.
3. Select Histogram and click Okay.
4. Select the Input range.
5. Click the Bin Range box and select the range you want.
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6. Then, click on the Output Range option, click in the Output Range box and select any cell.
7. Check final Chart Output and label them.
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