Statistics is the scientific and mathematical analysis that uses quantified models, representations, etc. for collecting, interpreting, analysing and presenting empirical data. The presentation focuses on the significance of statistics, statistics as a career choice, varied career paths in statistics, various data types in statistics, etc.

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2. Statistics
Statistics is the scientific study
of collecting, interpreting,
analyzing and presenting
empirical data.
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3. Importance of Statistics
•Helps in weather forecasting
•Used by researchers t collect
relevant data
•Used by business firms to calculate
risks related to insurance
•Used in the investment market
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4. •Used in interpreting reliable
conclusions
•Helpful in medical studies
•Used for quality testing
•Used for collecting data in
political campaigns
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5. Branches of Statistics
It’s important to study the
branches of statists to get a
holistic point of view for the
whole concept. Statistics deals
mainly in two branches i.e.
Descriptive Statistics and
Inferential Statistics.
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6. Descriptive Statistics
•This deals with the
presentation and collection
of data. It provides a brief
summary of data in
numerical or graphic form.
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7. Inferential Statistics
•This deals with the study of drawing valid conclusions from
the statistical analysis performed using descriptive statistics .it
is mostly used to make an inference and describe the
population.
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8. Statistical data
Data is the actual piece of
information collected through
studies conducted. It’s important to
understand statistical data types
because you can use certain
statistical measurements only for
specific data types.
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9. Most data are categorized under two categories i.e. numerical
data and categorical data.
•Categorical Data- this
represents the data related to
characteristics like a person’s
gender, language, etc. there are
two types of categorical data:-
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10. •Nominal data-theses values represent label units and discrete
values that have no quantitative value.
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•Ordinal Data- these data represent
numerically and ordered units. These
values are ordered.

11. •Numerical Data- this represents the
data which have the meaning as a
measurement like a person’s height,
weight, etc. there are two types of
numerical data:-
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12. •Discrete Data- the data in which values are separated and
discrete. These values can be easily counted.
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•Continuous Data- the data in
which values cannot be counted,
but are measured. It generally
represents measurements.

13. The Categorization of data types is
important as you can only use a certain
measurement tool for a particular type of
data. The distinction of numerical data
and categorical data are done for drawing
valid conclusions and for having a reliable
analysis. Thus, knowing the types of data
you are dealing with enables you to
choose the correct method of analysis.
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Why data types are important?

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Varied Career positions in statistics
1. Statistician
2. Biometrician
3. Mudlogger
4. Royalty Calculation Analyst
5. Scientist
6. Actuary
7. Senior Quantitative Analyst
8. Data scientist
9. Brand Optimization Analyst
There are numerous career paths for a statistics major student
can get withhold of these days. For example,

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