Data Analysis & Statistics: practical course for beginners
4.3 (122 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
18,380 students enrolled

Data Analysis & Statistics: practical course for beginners

Learn how to uncover the power of data analysis and statistics in this complete and easy to follow step-by-step course
4.3 (122 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
18,380 students enrolled
Created by Jacek Kułak
Last updated 7/2020
English
English [Auto]
Current price: $139.99 Original price: $199.99 Discount: 30% off
23 hours left at this price!
30-Day Money-Back Guarantee
This course includes
  • 7.5 hours on-demand video
  • 19 articles
  • 13 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Assignments
  • Certificate of Completion
Training 5 or more people?

Get your team access to 4,000+ top Udemy courses anytime, anywhere.

Try Udemy for Business
What you'll learn
  • How to analyze data and how to use statistics in practice
  • How to predict or explain different behaviors and events
  • How to prepare data for the analysis
  • How to collect data
  • How to create a survey
  • How to visualize data
  • How to find ideas for data research
  • How to tell the story through data
  • How to draw conclusions and have profits from the results of your data analysis
Requirements
  • Everyone can take this course, no experience is needed. We will go step-by-step from the very beginning
  • Just some time and willingness to learn
Description

Find out why data planning is like a bank robbery and why you should explore data like Indiana Jones. Get to know the poisonous triangle of data collection and see how data can be spoiled during preparation with one bad ingredient. Learn why data analysis itself is the cherry on top and understand why data analysis is all about the money and what to do about it.

If you ever wanted to learn data analysis and statistics, but thought it was too complicated or time consuming, you’re in the right place. Start using powerful scientific methods in a simple way. This is the data analysis and statistics course you’ve been waiting for. Practical, easy to understand, straight to the point.

This course will give you the complete package to be very effective in analyzing data and using statistics. Throughout the course we will use the mobile shopping case study, which makes learning fun along the way.


Main features of this course:

  • Provides you the complete package to be comfortable using statistics and analyzing data

  • Covers all stages of data analysis process

  • Very easy to understand

  • No complicated equations

  • Plain English instead of multiple statistical terms

  • Practical, with mobile shopping case study

  • Exercises and quizzes to help you master data analysis and statistics

  • Real world dataset and other materials to download

  • More than 70 high quality videos


Why should you take this course?

Data analysis is becoming more and more popular and important every year. You don’t have to become data science guru or master of data mining overnight, but you should know how to analyze and use data in practice. You should be able to effectively work with real world, business data on your own. And this course is all about giving you just that in the quickest and easiest way possible. You won’t waste time for theoretical concepts relevant to geeks and teachers only. We will dive directly into the key knowledge and methods.

You will follow the intuitive step-by-step process, with examples, quizzes and exercises. The same process that is utilized by the most successful companies. At the end of the course you will feel comfortable with data analysis tasks and use of the most important statistics. This course is a first step you need to take into the world of professional data analysis and you don’t need any experience to take it. Go beyond Excel analysis and surprise your boss with valuable insight. Or learn for the benefit of your own company. Whatever is your motivation to start with data analysis and statistics, you’re in the right place.

This complete course is divided into six essential chapters that corresponds with the six parts of data analysis process - data planning, data exploration, data collection, data preparation, data analysis and data monetization. All of this explained in a pleasant and accessible way, just like your colleague would explain this to you. And obviously you have 30 days money back guarantee, if you don’t like this course for any reason. But I do everything in my power for you not only to like the course, but to love it.

A lot of people will tell you that you have to learn programming languages to analyze data effectively, but it’s not true and you will see it in this course. Programming background is nice, but you don’t have to know any programming language to uncover the power of data. Understanding data analysis and statistics is not far away. It is the key competence on the job market, but also in everyday life. Remember that no great decision has ever been made without it. Sign up for this course today and immediately improve the skills essential for your success.




Who this course is for:
  • It’s for you, if you want to make informed decisions based on data
  • It’s for you, if you want to be more efficient in your work
  • It’s for you, if you want to update or develop your skills and analyze data the right way
  • It’s for you, if you are interested in data analysis or statistics
  • It’s for you, if the content of other courses turned out to be difficult to understand
Course content
Expand all 93 lectures 07:38:52
+ Introduction - the adventure begins
1 lecture 02:33

Information about the course. Presentation of the data analysis case study. You will know what will be covered in the course.

Preview 02:33
+ Data planning - it's like a bank robbery.
9 lectures 28:08

Summary of the section. You will know the importance of data planning.

Preview 01:09

How to start data analysis process presented on a series of examples. You will be able to set data analysis goals and define what information and data are needed to achieve these goals.

Preview 04:57
In this assignment you will set your own data analysis goals.
#1: Plan your project
1 question

Illustration of an analyst's dillema between choosing data analysis method and data collection method. You will know how to make the correct choice.

What was first, the chicken or the egg?
01:15

Comparison of qualitative and quantitative data. You will know the differences between the two and what they mean to your business case.

Two types of data
02:19

Check whether you know the difference between qualitative and quantitative data

Qualitative vs quantitative data
6 questions

The summary of the most popular data analysis methods. You will be able to choose the correct method according to your requirements.

Choose data analysis method
04:34

Presentation of 3 main ways to find your data. You will know your options in terms of data collection.

How to find data?
01:30

Comparison of free and paid sources of already collected data. You will know where to look for already collected data and pros and cons of this option.

Option 1: Find data already collected by someone else
04:01

Cooperation with research companies. You will know the 3 step process of ordering collection of data to the research company and whether it's worth to do that.

Option 2: Order collection of data to the research company
07:13

Why you should consider collecting data on your own in the first place. You will learn the next steps for this data collection method.

Option 3: Collect data by yourself
01:10

Check whether you know the main concepts of data planning stage

Data planning chapter summary
3 questions
+ Data exploration - Indiana Jones and the uncharted territories of data
11 lectures 25:39

Summary of the section. You will know the importance of data exploration.

Data exploration overview. Why is it important/ What you will learn?
01:22

Where and who to observe. You will know how to draw conclusions from observing people from your target group.

Explore data through observation
01:54

Start talking about the topic of your data analysis project. You will know how to extract useful information from conversations.

Explore data through interviews
02:57

Exploration of different text sources like websites, reports, magazines and books. You will know how to work with them for the benefit of your project.

Explore data through reading
03:12

Why scientific articles stand out from other sources of information and ideas for your project? You will know how to use scientific articles for your benefit in a fast and efficient way.

Explore data through scientific articles
06:01

Covering TV, radio and events as sources of information. You will know the useful alternatives to the most popular sources in terms of data exploration.

Explore data through other sources
02:13

You will explore data with different sources for your own project.

Assignment #2: Become data explorer
00:33

Review of all collected information from the exploration stage. You will know what to do with duplicated information, what are the rules in terms of variable naming and how to apply them.

Remove duplicate information and name your variables
04:25

You will clean up the information you have gathered and name your variables.

Assignment #3: Bring the order
01:01

Connecting all information. You will know how to draw a model based on the information you have gathered.

Create a model for data analysis
01:53

You will create a model for your data analysis project.

Assignment #4: Create your model
00:07

Check whether you know the main concepts of data exploration stage

Data exploration chapter summary
3 questions
+ Data collection - the poisonous triangle
17 lectures 01:16:43

Summary of the section. You will know the importance of data collection.

Data collection overview. Why is it important/ What you will learn?
02:28

Different methods of respondents selection. You will know representative sample and its alternatives.

How to choose respondents?
06:04

Defining the size of the group for your analysis. You will know how many respondents you should have at minimum.

Choose the size of your sample
04:39

Check your knowledge regarding sample selection

Sample selection
3 questions

You will find the right number of respondents for your business case.

Assignment #5: Define the sample size
00:12

10 rules to follow while creating a survey. You will know how to make your survey successful.

Create a survey - general guidelines
05:49

Review of the types of questions available for a survey. You will know how to choose the correct type of questions in different situations.

Create a survey - choose type of questions
02:21

Summary of the two main types of variable measurement. You will know how to decide between reflective and formative measurement.

Create a survey - choose type of variable measurement
03:45

Comparison of nominal, ordinal, interval and ratio scales. You will know how to choose the correct measurement scale for your variable.

Create a survey - choose measurement scales
06:31

Check your knowledge regarding measurement scales

Measurement scales
4 questions

Creating a survey according to the rules and guidelines from the previous videos. You will know how to write a survey from scratch.

Create a survey - write the actual survey
14:40

You will create a complete survey adjusted to your business case in a note app/software.

Assignment #6: Create a survey
00:27

All information about testing your survey. You will know how to improve quality of your survey and avoid costly mistakes.

Test your survey
02:30

You will conduct test study and collect feedback for your business case.

Assignment #7: Conduct test study
00:11

Comparison of the most important data collection methods including in-person, telephone, mail and on-line. You will know pros, cons and application of each method.

Data collection methods
03:53

Using Google Forms to take survey into digital. You will know Google Forms tool in depth.

Data collection – on-line method with Google Forms in detail
19:24

You will prepare digital, interactive version of your survey.

Assignment #8: Take your Survey to Digital
00:34

Tips and advices to attract more respondents. You will know free and paid possibilities to gain visibility for your survey.

Promote your survey
02:46

You will promote your survey to get all responses you need.

Assignment #9: Promotion time
00:28

Check whether you know the main concepts of data collection stage

Data collection chapter summary
5 questions
+ Data preparation - don't spoil the dish
12 lectures 01:12:41

Summary of the section. You will know the importance of data preparation.

Data preparation overview. Why is it important/ What you will learn?
03:32

Closer look at the Mobile Shopping dataset. You will know what to look for in your own dataset.

Examine your dataset
03:33

The reasons of unwanted data and how to deal with them. You will know how to recognize unwanted data and what to do about it.

Remove unwanted data
06:49

Causes and consequences of missing data. You will know when it is ok to have missing data and when it is not, how to find and replace missing data.

Identify and mark missing data
07:09

Covering five key areas of data formatting - whitespaces, typos, capitalization, data units and data types. You will know what formatting you should have to save time, effort and errors.

Data formatting - five things to look out for
03:21

Why white spaces can mess up your results. You will be able to identify white spaces and remove them from your dataset using couple of different options.

Get rid of white spaces
03:39

How typos can affect your data presented on example, and ways to solve typos problem. You will know how to identify and correct typos with charts, filtering, find and replace and simple regular expressions.

Correct typos
06:24

Functions and add-ons in Google Sheets dedicated to consistent capitalization. You will know how to ensure particular capitalization for all variables, including title case, sentence case, upper case, lower case.

Ensure consistent capitalization
04:03

Explanation when unit of your data is incorrect and what are the necessary changes in such case. You will be able to decide (and implement) between conversion of data to the correct data type and removal.

Change incompatible data units
06:28

Review of the available data types and when data type is wrongly assigned. You will be able to choose and assign the right data type for each variable.

Assign the right data types
05:35

Conversion of data to the required format, structure and content. You will be able to transform your data to work properly with different types of methods, software and procedures.

Data transformation. Convert your data to meet the requirements
21:47

You will prepare your data according to all data preparation rules and guidelines.

Assignment #10: Clean and Transform
00:21

Check whether you know the main concepts of data preparation stage

Data preparation chapter summary
4 questions
+ Data analysis - cherry on top
31 lectures 03:02:53

Summary of the section. You will know the importance of data analysis.

Data analysis overview. Why is it important/ What you will learn?
02:35

Descriptive statistics measures presented on easy to follow example. You will know how to calculate basic descriptive statistics such as mean, median, mode, range, standard deviation and more.

Preview 09:35

Review of the essential data distributions. Basic measures and guidelines. You will be able to check whether your data is normally distributed.

Data distribution. Is your data normal?
10:33

Implementation of descriptive statistics learned in the theory part for the Mobile Shopping dataset. You will be able to apply the most important descriptive statistics in practice.

Practical use of descriptive statistics
22:27

You will calculate descriptive statistics for your business case.

Assignment #11: Calculate descriptive statistics
00:07

The history of inferential statistics and the presentation of the most important inferential statistics. You will know how analysis of variance, regression and structural equation modelling work.

What are inferential statistics and how they work for data analysis?
10:35

Check your knowledge regarding descriptive and inferential statistics

Descriptive vs inferential statistics
6 questions

Review of the available statistical software for PLS-SEM method with pros, cons and pricing. You will know how to choose a statistical software according to your needs and requirements.

Choose statistical software according to your data analysis method
04:04

Downloading SmartPLS 3 software from the official website. You will know how to download and install SmartPLS 3 software.

Download statistical software
05:56

You will download Smart PLS3 software.

Assignment #12: Download SmartPLS 3 software
00:09

Walk through SmartPLS 3 software, summary of the possibilities, settings. You will know how to use all necessary options in SmartPLS 3 software.

Touring the interface
11:27

Setting up your data analysis project. You will be able to create data analysis project and import data for this project inside SmartPLS 3.

Create a project and import data
03:30

You will create your data analysis project and import data for this project.

Preview 00:12

Review of all required steps for the creation of the groups including settings. You will know how to create different groups of respondents inside SmartPLS 3.

Create data groups
05:18

You will create different groups of respondents for your business case.

Assignment #14: Create data groups for your project
00:07

Create a digital version of a model for your data analysis, adjust the look and feel. You will know how to correctly create a model and include all relationships between variables inside SmartPLS 3 software.

Create a model in the statistical software
06:30

You will create a model for your business case.

Assignment #15: Create a model for your project
00:11

Summary of methods and procedures with explanation how they work. You will know what methods and procedures to use in SmartPLS 3 to receive required results and to achieve your goals.

Time to analyze. Methods and procedures. What options do you have?
05:56

Definition of reliability and importance of establishing reliability of your results. You will be able to check reliability of your results inside SmartPLS 3 software.

Reliability of your results. Let’s talk about consistency
07:10

You will check whether your results are consistent and stable.

Assignment #16: Check the reliability for your data analysis
00:06

Definition of validity and importance of establishing validity of your results. You will be able to check validity of your results inside SmartPLS 3 software.

Validity of your results. Let’s talk about the truth
06:35

You will check whether your results are true and accurate.

Assignment #17: Check the validity for your data analysis
00:06

Covering model fit concept and its metrics. You will know how to check the goodness of fit measure.

Model Fit. How good is your model?
02:08

Things you should consider while generating results for your data analysis project. You will be able to check the most important results including: path coefficients, statistical significance and R square value.

Main results - the heart of your analysis
09:38

Summary of ways to check differences between groups for different data analysis methods. You will be able to check differences in behavior for different groups of respondents.

Results for different groups. On the trail of diversity
10:32

Explanation of mediation concept on two examples. You will be able to check mediation reationships in your data analysis project.

Mediation results. Looking for a middleman
09:26

Presentation of different export options. You will be able to export your data to different formats in SmartPLS 3.

Export your data
03:05

Practical conclusions for each relationship inside your model. What your results tell about consumers, what do they mean for your company and business in general. You will be able to interpret your results and prepare valuable business recommendations.

Results interpretation - main results for the general group
22:12

You will propose business recommendations based on your main results.

Assignment #18: What your results mean - part 1
00:25

Providing more precise suggestions to business by looking at the results of different groups of respondents separately and covering the potential mediation effect. You will be able to give different recommendations from your results for different groups of people and know what type of mediation occured and how it affects your conclusions.

Results interpretation - group analysis and mediation
06:29

You will propose business recommendations based on the results of your group analysis.

Assignment #19: What your results mean - part 2
00:18

Limitiations of your data analysis project, things that were not covered. You will be able to plan your future data analysis project and improve its quality.

Optimize your future data analysis
05:30

Check whether you know the main concepts of actual data analysis stage

Data analysis chapter summary
6 questions
+ Data monetization - it’s all about the money
8 lectures 57:13

Summary of the section. You will know the importance of data monetization.

Data monetization and usage overview. Why is it important/ What you will learn?
02:02

Top ten best practices and guidelines on how to visualize your data. You will be able to tell the story through data and transform data to a good looking insights.

Data visualization. How to deliver your story?
07:31

Comparison of pros, cons and usage of the most useful charts. You will have no problem with choosing the right chart type for each situation.

Different chart types
05:35
Chart types quiz
4 questions

Visualization of data in Google Slides. You will be able to use Google Slides to make your data look more attractive to the user.

Data visualization in practise - create the wow effect
29:44

You will prepare the visualization of your results to make them more accessible and interesting.

Assignment #20: Visualize your results
00:07

Turning recommendations from data analysis into practical implementation. You will know how to prepare to the implementation meeting including dealing with the attitudes of your coworkers.

How to use your results for the product development?
05:41

Comparison of generating money from your data analysis report vs selling data. You will know how to make revenue from your data analysis project.

How to use your results for sales?
03:44

Presentation of the main marketing activities that can be done after your data analysis is finished. You will know how to use your data analysis report to ensure it has the full exposure in front of people who are important for your business.

How to use your results for marketing?
02:49

Check whether you know the main concepts of data monetization stage

Data monetization chapter summary
3 questions
+ Conclusion and next steps - there is no finish line
1 lecture 03:08

Summary of the course. You will see what you have learned throughout the course and where to go from here.

Conclusion
03:08
+ Bonus - there’s always more
3 lectures 09:52

Summary of the section. You will know what type of content will be added in the future.

How the bonus section will be developed?
00:36

Formative measurement presented on the Corporate Reputation Project example. You will be able to measure variable in a formative way with required measures.

Formative measurement analysis
06:15

F square as a supplement or alternative to the traditional approach of the variable measurement. You will be able to interpret f square value for your data analysis project.

Effect size f square - are my results meaningful?
03:01