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Business Business Analytics & Intelligence Data Analysis

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
Rating: 4.1 out of 54.1 (246 ratings)
36,408 students
Created by Jacek Kułak
Last updated 7/2020
English
English [Auto]
30-Day Money-Back Guarantee

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

9 sections • 93 lectures • 7h 38m total length

  • Preview02:33

  • Preview01:09
  • Preview04:57
  • #1: Plan your project
    1 question
  • What was first, the chicken or the egg?
    01:15
  • Two types of data
    02:19
  • Qualitative vs quantitative data
    6 questions
  • Choose data analysis method
    04:34
  • How to find data?
    01:30
  • Option 1: Find data already collected by someone else
    04:01
  • Option 2: Order collection of data to the research company
    07:13
  • Option 3: Collect data by yourself
    01:10
  • Data planning chapter summary
    3 questions

  • Data exploration overview. Why is it important/ What you will learn?
    01:22
  • Explore data through observation
    01:54
  • Explore data through interviews
    02:57
  • Explore data through reading
    03:12
  • Explore data through scientific articles
    06:01
  • Explore data through other sources
    02:13
  • Assignment #2: Become data explorer
    00:33
  • Remove duplicate information and name your variables
    04:25
  • Assignment #3: Bring the order
    01:01
  • Create a model for data analysis
    01:53
  • Assignment #4: Create your model
    00:07
  • Data exploration chapter summary
    3 questions

  • Data collection overview. Why is it important/ What you will learn?
    02:28
  • How to choose respondents?
    06:04
  • Choose the size of your sample
    04:39
  • Sample selection
    3 questions
  • Assignment #5: Define the sample size
    00:12
  • Create a survey - general guidelines
    05:49
  • Create a survey - choose type of questions
    02:21
  • Create a survey - choose type of variable measurement
    03:45
  • Create a survey - choose measurement scales
    06:31
  • Measurement scales
    4 questions
  • Create a survey - write the actual survey
    14:40
  • Assignment #6: Create a survey
    00:27
  • Test your survey
    02:30
  • Assignment #7: Conduct test study
    00:11
  • Data collection methods
    03:53
  • Data collection – on-line method with Google Forms in detail
    19:24
  • Assignment #8: Take your Survey to Digital
    00:34
  • Promote your survey
    02:46
  • Assignment #9: Promotion time
    00:28
  • Data collection chapter summary
    5 questions

  • Data preparation overview. Why is it important/ What you will learn?
    03:32
  • Examine your dataset
    03:33
  • Remove unwanted data
    06:49
  • Identify and mark missing data
    07:09
  • Data formatting - five things to look out for
    03:21
  • Get rid of white spaces
    03:39
  • Correct typos
    06:24
  • Ensure consistent capitalization
    04:03
  • Change incompatible data units
    06:28
  • Assign the right data types
    05:35
  • Data transformation. Convert your data to meet the requirements
    21:47
  • Assignment #10: Clean and Transform
    00:21
  • Data preparation chapter summary
    4 questions

  • Data analysis overview. Why is it important/ What you will learn?
    02:35
  • Preview09:35
  • Data distribution. Is your data normal?
    10:33
  • Practical use of descriptive statistics
    22:27
  • Assignment #11: Calculate descriptive statistics
    00:07
  • What are inferential statistics and how they work for data analysis?
    10:35
  • Descriptive vs inferential statistics
    6 questions
  • Choose statistical software according to your data analysis method
    04:04
  • Download statistical software
    05:56
  • Assignment #12: Download SmartPLS 3 software
    00:09
  • Touring the interface
    11:27
  • Create a project and import data
    03:30
  • Preview00:12
  • Create data groups
    05:18
  • Assignment #14: Create data groups for your project
    00:07
  • Create a model in the statistical software
    06:30
  • Assignment #15: Create a model for your project
    00:11
  • Time to analyze. Methods and procedures. What options do you have?
    05:56
  • Reliability of your results. Let’s talk about consistency
    07:10
  • Assignment #16: Check the reliability for your data analysis
    00:06
  • Validity of your results. Let’s talk about the truth
    06:35
  • Assignment #17: Check the validity for your data analysis
    00:06
  • Model Fit. How good is your model?
    02:08
  • Main results - the heart of your analysis
    09:38
  • Results for different groups. On the trail of diversity
    10:32
  • Mediation results. Looking for a middleman
    09:26
  • Export your data
    03:05
  • Results interpretation - main results for the general group
    22:12
  • Assignment #18: What your results mean - part 1
    00:25
  • Results interpretation - group analysis and mediation
    06:29
  • Assignment #19: What your results mean - part 2
    00:18
  • Optimize your future data analysis
    05:30
  • Data analysis chapter summary
    6 questions

  • Data monetization and usage overview. Why is it important/ What you will learn?
    02:02
  • Data visualization. How to deliver your story?
    07:31
  • Different chart types
    05:35
  • Chart types quiz
    4 questions
  • Data visualization in practise - create the wow effect
    29:44
  • Assignment #20: Visualize your results
    00:07
  • How to use your results for the product development?
    05:41
  • How to use your results for sales?
    03:44
  • How to use your results for marketing?
    02:49
  • Data monetization chapter summary
    3 questions

  • Conclusion
    03:08

  • How the bonus section will be developed?
    00:36
  • Formative measurement analysis
    06:15
  • Effect size f square - are my results meaningful?
    03:01

Instructor

Jacek Kułak
Digital Marketing Native
Jacek Kułak
  • 4.2 Instructor Rating
  • 468 Reviews
  • 58,734 Students
  • 2 Courses

Professional with over 10 years of digital marketing experience from the world’s biggest organizations including 5+ years in The Walt Disney Company and 5+ years in various creative agencies. PhD in marketing at the University of Warsaw and the author of multiple digital marketing articles. Digital marketing passionate who loves to teach.

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