Basic Descriptive statistics

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Descriptive statistics is used to describe and summarize key characteristics of a data set. Commonly used measures include central tendency, such as the mean, median, and mode, and measures of dispersion like range, interquartile range, standard deviation, and variance. The mean is the average value calculated by summing all values and dividing by the number of values. The median is the middle value when data is arranged in order. The mode is the most frequently occurring value. Measures of dispersion describe how spread out the data is, such as the difference between highest and lowest values (range) or how close values are to the average (standard deviation).

Basic Statistics : Descriptive Statistics

What is Descriptive
Statistics ? “ This is the statistics which deals with
descriptive section of the data set as well
as have tendency to describe the data set
initially ”

Commonly used measures to describe a data set :
 Measures of Central Tendency
 Measures of dispersion

Measures of Central Tendency:
A measure of central tendency is a single value
that attempts to describe a set of data by
identifying the central position within that set of
data. The mean, median and mode are most
likely the measures of central tendency that we
are most familiar with.
Mean (Arithmetic) :
The mean (or average ) is equal to the sum of all
the values in the data set divided by the number
of values in the data set. So, if we have n values in
a data set and they have values x1, x2, ..., xn, the
sample mean, usually denoted by (pronounced x
bar), is:

Median
The median is the middle score for a set of data that has been arranged in order
of magnitude.
Mode :
The mode is the value that appears most often in a set of data.

Measures of dispersion
Range:
The spread, or the distance, between the
lowest and highest values of a variable.
Interquartile Range:
A quartile is the value that marks one of the
divisions that breaks a series of values into
four equal parts. The Interquartile range is
the distance or range between the 25th
percentile and the 75th percentile.

Standard Deviation:
The standard deviation gives an idea of how close the entire set of data is to the average value.
Variance:
Measures how far a set of numbers is spread out. A variance of zero indicates that all the values
are identical. Variance is always non-negative, a small variance indicates that the data points
tend to be very close to the mean (Average value), while a high variance indicates that the data
points are very spread out around the mean.

1. The document discusses descriptive statistics, which is the study of how to collect, organize, analyze, and interpret numerical data. 2. Descriptive statistics can be used to describe data through measures of central tendency like the mean, median, and mode as well as measures of variability like the range. 3. These statistical techniques help summarize and communicate patterns in data in a concise manner.

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Deloitte - A Framework for Process Mining ProjectsProcess mining Evangelist

Tijn van der Heijden is a business analyst with Deloitte. He learned about process mining during his studies in a BPM course at Eindhoven University of Technology and became fascinated with the fact that it was possible to get a process model and so much performance information out of automatically logged events of an information system. Tijn successfully introduced process mining as a new standard to achieve continuous improvement for the Rabobank during his Master project. At his work at Deloitte, Tijn has now successfully been using this framework in client projects.

Automation Platforms and Process Mining - success storyProcess mining Evangelist

Zig Websoftware creates process management software for housing associations. Their workflow solution is used by the housing associations to, for instance, manage the process of finding and on-boarding a new tenant once the old tenant has moved out of an apartment. Paul Kooij shows how they could help their customer WoonFriesland to improve the housing allocation process by analyzing the data from Zig's platform. Every day that a rental property is vacant costs the housing association money. But why does it take so long to find new tenants? For WoonFriesland this was a black box. Paul explains how he used process mining to uncover hidden opportunities to reduce the vacancy time by 4,000 days within just the first six months.

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Basic Descriptive statistics

1. Basic Statistics : Descriptive Statistics

2. What is Descriptive Statistics ? “ This is the statistics which deals with descriptive section of the data set as well as have tendency to describe the data set initially ”

3. Commonly used measures to describe a data set :  Measures of Central Tendency  Measures of dispersion

4. Measures of Central Tendency: A measure of central tendency is a single value that attempts to describe a set of data by identifying the central position within that set of data. The mean, median and mode are most likely the measures of central tendency that we are most familiar with. Mean (Arithmetic) : The mean (or average ) is equal to the sum of all the values in the data set divided by the number of values in the data set. So, if we have n values in a data set and they have values x1, x2, ..., xn, the sample mean, usually denoted by (pronounced x bar), is:

5. Median The median is the middle score for a set of data that has been arranged in order of magnitude. Mode : The mode is the value that appears most often in a set of data.

6. Measures of dispersion Range: The spread, or the distance, between the lowest and highest values of a variable. Interquartile Range: A quartile is the value that marks one of the divisions that breaks a series of values into four equal parts. The Interquartile range is the distance or range between the 25th percentile and the 75th percentile.

7. Standard Deviation: The standard deviation gives an idea of how close the entire set of data is to the average value. Variance: Measures how far a set of numbers is spread out. A variance of zero indicates that all the values are identical. Variance is always non-negative, a small variance indicates that the data points tend to be very close to the mean (Average value), while a high variance indicates that the data points are very spread out around the mean.

8. Thank You

Basic Descriptive statistics

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