Data Analysis & Statistics: practical course for beginners
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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:
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Provides you the complete package to be comfortable using statistics and analyzing data
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Covers all stages of data analysis process
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Very easy to understand
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No complicated equations
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Plain English instead of multiple statistical terms
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Practical, with mobile shopping case study
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Exercises and quizzes to help you master data analysis and statistics
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Real world dataset and other materials to download
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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.
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Data planning overview. Why it is important/ What you will learn?Summary of the section. You will know the importance of data planning.
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Where to start?
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.
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Assignment #1: Plan your projectIn this assignment you will set your own data analysis goals.
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#1: Plan your project
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What was first, the chicken or the egg?
Illustration of an analyst's dillema between choosing data analysis method and data collection method. You will know how to make the correct choice.
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Two types of data
Comparison of qualitative and quantitative data. You will know the differences between the two and what they mean to your business case.
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Qualitative vs quantitative dataCheck whether you know the difference between qualitative and quantitative data
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Choose data analysis method
The summary of the most popular data analysis methods. You will be able to choose the correct method according to your requirements.
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How to find data?
Presentation of 3 main ways to find your data. You will know your options in terms of data collection.
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Option 1: Find data already collected by someone else
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.
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Option 2: Order collection of data to the research company
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.
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Option 3: Collect data by yourself
Why you should consider collecting data on your own in the first place. You will learn the next steps for this data collection method.
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Data planning chapter summary
Check whether you know the main concepts of data planning stage
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Data exploration overview. Why is it important/ What you will learn?
Summary of the section. You will know the importance of data exploration.
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Explore data through observation
Where and who to observe. You will know how to draw conclusions from observing people from your target group.
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Explore data through interviews
Start talking about the topic of your data analysis project. You will know how to extract useful information from conversations.
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Explore data through reading
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.
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Explore data through scientific articles
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.
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Explore data through other sources
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.
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Assignment #2: Become data explorer
You will explore data with different sources for your own project.
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Remove duplicate information and name your variables
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.
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Assignment #3: Bring the order
You will clean up the information you have gathered and name your variables.
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Create a model for data analysis
Connecting all information. You will know how to draw a model based on the information you have gathered.
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Assignment #4: Create your model
You will create a model for your data analysis project.
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Data exploration chapter summary
Check whether you know the main concepts of data exploration stage
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Data collection overview. Why is it important/ What you will learn?
Summary of the section. You will know the importance of data collection.
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How to choose respondents?
Different methods of respondents selection. You will know representative sample and its alternatives.
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Choose the size of your sample
Defining the size of the group for your analysis. You will know how many respondents you should have at minimum.
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Sample selection
Check your knowledge regarding sample selection
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Assignment #5: Define the sample size
You will find the right number of respondents for your business case.
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Create a survey - general guidelines
10 rules to follow while creating a survey. You will know how to make your survey successful.
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Create a survey - choose type of questions
Review of the types of questions available for a survey. You will know how to choose the correct type of questions in different situations.
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Create a survey - choose type of variable measurement
Summary of the two main types of variable measurement. You will know how to decide between reflective and formative measurement.
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Create a survey - choose measurement scales
Comparison of nominal, ordinal, interval and ratio scales. You will know how to choose the correct measurement scale for your variable.
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Measurement scales
Check your knowledge regarding measurement scales
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Create a survey - write the actual survey
Creating a survey according to the rules and guidelines from the previous videos. You will know how to write a survey from scratch.
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Assignment #6: Create a survey
You will create a complete survey adjusted to your business case in a note app/software.
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Test your survey
All information about testing your survey. You will know how to improve quality of your survey and avoid costly mistakes.
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Assignment #7: Conduct test study
You will conduct test study and collect feedback for your business case.
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Data collection methods
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.
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Data collection – on-line method with Google Forms in detail
Using Google Forms to take survey into digital. You will know Google Forms tool in depth.
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Assignment #8: Take your Survey to Digital
You will prepare digital, interactive version of your survey.
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Promote your survey
Tips and advices to attract more respondents. You will know free and paid possibilities to gain visibility for your survey.
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Assignment #9: Promotion time
You will promote your survey to get all responses you need.
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Data collection chapter summary
Check whether you know the main concepts of data collection stage
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Data preparation overview. Why is it important/ What you will learn?
Summary of the section. You will know the importance of data preparation.
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Examine your dataset
Closer look at the Mobile Shopping dataset. You will know what to look for in your own dataset.
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Remove unwanted data
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.
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Identify and mark missing data
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.
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Data formatting - five things to look out for
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.
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Get rid of white spaces
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.
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Correct typos
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.
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Ensure consistent capitalization
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.
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Change incompatible data units
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.
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Assign the right data types
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.
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Data transformation. Convert your data to meet the requirements
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.
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Assignment #10: Clean and Transform
You will prepare your data according to all data preparation rules and guidelines.
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Data preparation chapter summary
Check whether you know the main concepts of data preparation stage
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Data analysis overview. Why is it important/ What you will learn?
Summary of the section. You will know the importance of data analysis.
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What are descriptive statistics and how they work for data analysis?
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.
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Data distribution. Is your data normal?
Review of the essential data distributions. Basic measures and guidelines. You will be able to check whether your data is normally distributed.
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Practical use of descriptive statistics
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.
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Assignment #11: Calculate descriptive statistics
You will calculate descriptive statistics for your business case.
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What are inferential statistics and how they work for data analysis?
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.
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Descriptive vs inferential statistics
Check your knowledge regarding descriptive and inferential statistics
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Choose statistical software according to your data analysis method
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.
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Download statistical software
Downloading SmartPLS 3 software from the official website. You will know how to download and install SmartPLS 3 software.
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Assignment #12: Download SmartPLS 3 software
You will download Smart PLS3 software.
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Touring the interface
Walk through SmartPLS 3 software, summary of the possibilities, settings. You will know how to use all necessary options in SmartPLS 3 software.
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Create a project and import data
Setting up your data analysis project. You will be able to create data analysis project and import data for this project inside SmartPLS 3.
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Assignment #13: Create your project and import data
You will create your data analysis project and import data for this project.
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Create data groups
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.
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Assignment #14: Create data groups for your project
You will create different groups of respondents for your business case.
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Create a model in the statistical software
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.
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Assignment #15: Create a model for your project
You will create a model for your business case.
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Time to analyze. Methods and procedures. What options do you have?
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.
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Reliability of your results. Let’s talk about consistency
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.
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Assignment #16: Check the reliability for your data analysis
You will check whether your results are consistent and stable.
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Validity of your results. Let’s talk about the truth
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.
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Assignment #17: Check the validity for your data analysis
You will check whether your results are true and accurate.
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Model Fit. How good is your model?
Covering model fit concept and its metrics. You will know how to check the goodness of fit measure.
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Main results - the heart of your analysis
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.
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Results for different groups. On the trail of diversity
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.
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Mediation results. Looking for a middleman
Explanation of mediation concept on two examples. You will be able to check mediation reationships in your data analysis project.
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Export your data
Presentation of different export options. You will be able to export your data to different formats in SmartPLS 3.
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Results interpretation - main results for the general group
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.
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Assignment #18: What your results mean - part 1
You will propose business recommendations based on your main results.
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Results interpretation - group analysis and mediation
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.
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Assignment #19: What your results mean - part 2
You will propose business recommendations based on the results of your group analysis.
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Optimize your future data analysis
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.
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Data analysis chapter summary
Check whether you know the main concepts of actual data analysis stage
