Course details
This course isyour complete guidetostatistics
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 OLS 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 Probability theory like sample space, events, randomness and basic set theory. We will then move onto discussing conditional probability and introduce the concept of mutually exclusive events.
In the fourth module, we will discuss Probability Distributions and show the difference between a continuous and a discrete distribution focusing on Normal and Binomial distributions.
The next chapter will discuss Sampling Distributions and introduce the concept of Central Limit Theorem and why sampling is important. We will also link the Central Limit theorem to the normal distribution.
The sixth module will focus on confidence intervals and the use of intervals to determine centre of a distribution as opposed to a point estimate such as the mean. We will also discuss the relationship between the significance level (alpha) and the confidence level.
The last module will introduce the concepts of Significance Tests - what they are and aren'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 basically the go-to course for laying strong foundations of statistical concepts you want, and the explanation and examples provided are something which havent beendone in any other courseon this platform.
There are helpfulquizzesincluded in all sections that will help you to cement the concepts learnt. Also, we arecommitted to add new practice activitiesso that you can practicallyapply the concepts learntin this course.
Why should you start learningSTATISTICS NOW!
Jobs in Analytics Data is everywhere and with that is the need to have professionals who can interpret that data which will come with a good 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!
Why learn from us?
Save HUNDREDS of dollars and your time with the most effective training course ever created. Gain instant access to the exact training courses used to train over 1,000 beginners to become experts in understanding statistical concepts for day to day jobs and for analytics techniques and data interpretation.
Call us ambitious, but we are trying to save you time and money while giving you quality.
Dont work hard Work smart!
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 ofstatistics as applied to a wide variety of disciplines.
This coursecovers basicstatistics, such ascalculating averages, medians, modes, and standard deviations.With easy-to-understand examples combined with real-world applicationsfrom 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
Updated on 14 November, 2018 - Read Less
