Description
Why should you learn statistics now?
Jobs in Analytics
– Data is everywhere, and with that is the need to have professionals who can interpret that data which requires a solid understanding of statistical concepts
Demand
is only going to go up – With more organizations realizing the potential of statistics for their business, data analysts knowing statistics will excel over the ones just knowing technical tools. For a good Data Analyst, it is
THE
backbone!
Build your Career in Data Science, Artificial Intelligence and Data Analysis
- Statistics remains
the fundamental skill set
of those pursuing a career in Data Science, Deep Learning, Artificial Intelligence, Management Consulting, Financial Analysis
Improve your understanding of the world
-
Statistics is used in everyday life, to describe the stock market, house prices, economic performance, business and much much more. Improve your data literacy and equip yourself with the ability to communicate in the language of the future.
Why learn from us?
Save your time and your money with us by using the exact training courses that have been used to equip over 1000 beginners with statistical skills that they can apply to their day-to-day jobs
Leverage our real-world understanding and experience, with instruction from real-life analytics experts who have built their careers applying statistics to real business problems on a day-to-day basis
Develop your skills in Data Analytics & Data Science with our expanding range of high quality programs, that equip you with the real-world skills needed to succeed in the workplace of the future
What is Statistics all about?
Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics. In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression. The second part of the course is concerned with the basics of probability: calculating probabilities, probability distributions and sampling distributions. You need to know about these things in order to understand how inferential statistics work. The third part of the course consists of an introduction to methods of inferential statistics - methods that help us decide whether the patterns we see in our data are strong enough to draw conclusions about the underlying population we are interested in. We will discuss confidence intervals and significance tests. You will not only learn about all these statistical concepts, you will also be trained to calculate and generate these statistics yourself using freely available statistical software.
Statistics encompasses the collection, analysis, and interpretation of data and provides a framework for thinking about data. Statistics is used in many areas of scientific and social research, is critical to business and manufacturing, and provides the mathematical foundation for machine learning and data mining.
In this course, students will gain a comprehensive introduction to the concepts and techniques of statistics as applied to a wide variety of disciplines.
This course covers basic statistics, such as calculating averages, medians, modes, and standard deviations. With easy-to-understand examples combined with real-world applications from the worlds of business, sports, education, entertainment, and more.
This course provides you with the skills and knowledge you need to start analyzing data. You'll explore how to use data and apply statistics to real-life problems and situations
What will you learn?
This course is
your complete guide
to the fundamentals of
statistics
and
probability
1.
Descriptive Statistics
2.
Measures of Central Tendency
3.
Correlation
4.
Linear Regression
5.
Probability Theory
6.
Discrete and Continuous Probability Distributions
7.
Sampling Distributions
8.
Confidence Intervals
9.
Significance Tests.
The first chapter will focus on
one variable analysis
- we start with discussing the various
descriptive statistics
, how data can be represented using
frequency tables
and then move on to discussing
measures of central tendency and their interpretation
.
The second module will focus on
Correlation
and
Simple Linear
Regression
and show how these can be
calculated in Excel
using various formulae. We will then also discuss the interpretation of these results
The next module will focus on introducing the fundamental concepts of
Probability Theory
like the
sample space, events, randomness
and
basic set theory
. We will then move onto discussing
conditional probability
and introduce the concept of
mutually exclusive events
. You will also learn how to calculate probabilities within this section.
In the fourth module, we will discuss
Probability Distributions
and show the difference between a
continuous
and
discrete
distributions, using the
Normal
and
Binomial
distributions as key examples.
The next chapter will discuss
Sampling Distributions
and introduce the
Central Limit Theorem
and discuss
why sampling is important
. We will also link the Central Limit Theorem to the normal distribution and explain why this result is so
critical
to statistical analysis.
The sixth module will focus on
confidence intervals
and the use of intervals to estimate the true average or proportion of a distribution. We will also discuss the
relationship between the significance level (alpha) and the confidence level
and teach you how to generate your own confidence intervals in Excel.
The last module will introduce the concept of statistical
Hypothesis Testing
- what it can tell you and what it can't (i.e. you can't prove anything); how to define the
null and alternate hypotheses
correctly; getting the direction and 'tails' of your distribution correct and finally
Type I and Type II errors
with example and interpretations.
This course is
the go-to course for building a solid foundation in statistics and probability
,
not only teaching you the theory but giving you a comprehensive set of real examples you can work on which
hasn't been
seen
in any other course on this platform.
There are helpful
quizzes
included in all sections that will help you to cement the concepts learnt. Also, we are
committed to add new practice activities
so that you can practically
apply the concepts learnt
in this course.
Requrirements
Requirements
Microsoft Excel
Basic Mathematics and Algebra