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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

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

  • You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
  • No previous design experience is needed.
  • No previous Adobe XD skills are needed.

Course Content

27 sections • 95 lectures
Expand All Sections
1-Introduction - the adventure begins
1
1.1-Introduction
2-Data planning - it's like a bank robbery.
13
2.1-Data planning overview. Why it is important/ What you will learn?
2.2-Where to start?
2.3-Assignment #1: Plan your project
2.4-#1: Plan your project
2.5-What was first, the chicken or the egg?
2.6-Two types of data
2.7-Qualitative vs quantitative data
2.8-Choose data analysis method
2.9-How to find data?
2.10-Option 1: Find data already collected by someone else
2.11-Option 2: Order collection of data to the research company
2.12-Option 3: Collect data by yourself
2.13-Data planning chapter summary
3-Data exploration - Indiana Jones and the uncharted territories of data
12
3.1-Data exploration overview. Why is it important/ What you will learn?
3.2-Explore data through observation
3.3-Explore data through interviews
3.4-Explore data through reading
3.5-Explore data through scientific articles
3.6-Explore data through other sources
3.7-Assignment #2: Become data explorer
3.8-Remove duplicate information and name your variables
3.9-Assignment #3: Bring the order
3.10-Create a model for data analysis
3.11-Assignment #4: Create your model
3.12-Data exploration chapter summary
4-Data collection - the poisonous triangle
20
4.1-Data collection overview. Why is it important/ What you will learn?
4.2-How to choose respondents?
4.3-Choose the size of your sample
4.4-Sample selection
4.5-Assignment #5: Define the sample size
4.6-Create a survey - general guidelines
4.7-Create a survey - choose type of questions
4.8-Create a survey - choose type of variable measurement
4.9-Create a survey - choose measurement scales
4.10-Measurement scales
4.11-Create a survey - write the actual survey
4.12-Assignment #6: Create a survey
4.13-Test your survey
4.14-Assignment #7: Conduct test study
4.15-Data collection methods
4.16-Data collection – on-line method with Google Forms in detail
4.17-Assignment #8: Take your Survey to Digital
4.18-Promote your survey
4.19-Assignment #9: Promotion time
4.20-Data collection chapter summary
5-Data preparation - don't spoil the dish
13
5.1-Data preparation overview. Why is it important/ What you will learn?
5.2-Examine your dataset
5.3-Remove unwanted data
5.4-Identify and mark missing data
5.5-Data formatting - five things to look out for
5.6-Get rid of white spaces
5.7-Correct typos
5.8-Ensure consistent capitalization
5.9-Change incompatible data units
5.10-Assign the right data types
5.11-Data transformation. Convert your data to meet the requirements
5.12-Assignment #10: Clean and Transform
5.13-Data preparation chapter summary
6-Data analysis - cherry on top
33
6.1-Data analysis overview. Why is it important/ What you will learn?
6.2-What are descriptive statistics and how they work for data analysis?
6.3-Data distribution. Is your data normal?
6.4-Practical use of descriptive statistics
6.5-Assignment #11: Calculate descriptive statistics
6.6-What are inferential statistics and how they work for data analysis?
6.7-Descriptive vs inferential statistics
6.8-Choose statistical software according to your data analysis method
6.9-Download statistical software
6.10-Assignment #12: Download SmartPLS 3 software
6.11-Touring the interface
6.12-Create a project and import data
6.13-Assignment #13: Create your project and import data
6.14-Create data groups
6.15-Assignment #14: Create data groups for your project
6.16-Create a model in the statistical software
6.17-Assignment #15: Create a model for your project
6.18-Time to analyze. Methods and procedures. What options do you have?
6.19-Reliability of your results. Let’s talk about consistency
6.20-Assignment #16: Check the reliability for your data analysis
6.21-Validity of your results. Let’s talk about the truth
6.22-Assignment #17: Check the validity for your data analysis
6.23-Model Fit. How good is your model?
6.24-Main results - the heart of your analysis
6.25-Results for different groups. On the trail of diversity
6.26-Mediation results. Looking for a middleman
6.27-Export your data
6.28-Results interpretation - main results for the general group
6.29-Assignment #18: What your results mean - part 1
6.30-Results interpretation - group analysis and mediation
6.31-Assignment #19: What your results mean - part 2
6.32-Optimize your future data analysis
6.33-Data analysis chapter summary
7-Data monetization - it’s all about the money
10
7.1-Data monetization and usage overview. Why is it important/ What you will learn?
7.2-Data visualization. How to deliver your story?
7.3-Different chart types
7.4-Chart types quiz
7.5-Data visualization in practise - create the wow effect
7.6-Assignment #20: Visualize your results
7.7-How to use your results for the product development?
7.8-How to use your results for sales?
7.9-How to use your results for marketing?
7.10-Data monetization chapter summary
8-Conclusion and next steps - there is no finish line
1
8.1-Conclusion
9-Bonus - there’s always more
3
9.1-How the bonus section will be developed?
9.2-Formative measurement analysis
9.3-Effect size f square - are my results meaningful?