Data Analysis & Statistics: practical course for beginners

Data Analysis & Statistics: practical course for beginners, available at $64.99, has an average rating of 4.6, with 94 lectures, 11 quizzes, based on 646 reviews, and has 61114 subscribers.

You will learn about 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 This course is ideal for individuals who are It’s for you, if you want to make informed decisions based on data or It’s for you, if you want to be more efficient in your work or It’s for you, if you want to update or develop your skills and analyze data the right way or It’s for you, if you are interested in data analysis or statistics or It’s for you, if the content of other courses turned out to be difficult to understand It is particularly useful for It’s for you, if you want to make informed decisions based on data or It’s for you, if you want to be more efficient in your work or It’s for you, if you want to update or develop your skills and analyze data the right way or It’s for you, if you are interested in data analysis or statistics or It’s for you, if the content of other courses turned out to be difficult to understand.

Enroll now: Data Analysis & Statistics: practical course for beginners

Summary

Title: Data Analysis & Statistics: practical course for beginners

Price: $64.99

Average Rating: 4.6

Number of Lectures: 94

Number of Quizzes: 11

Number of Published Lectures: 94

Number of Published Quizzes: 11

Number of Curriculum Items: 106

Number of Published Curriculum Objects: 106

Original Price: zł549.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

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

Target Audiences

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

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.

Course Curriculum

Chapter 1: Introduction – the adventure begins

Lecture 1: Introduction

Chapter 2: Data planning – it's like a bank robbery.

Lecture 1: Data planning overview. Why it is important/ What you will learn?

Lecture 2: Where to start?

Lecture 3: Assignment #1: Plan your project

Lecture 4: What was first, the chicken or the egg?

Lecture 5: Two types of data

Lecture 6: Choose data analysis method

Lecture 7: How to find data?

Lecture 8: Option 1: Find data already collected by someone else

Lecture 9: Option 2: Order collection of data to the research company

Lecture 10: Option 3: Collect data by yourself

Chapter 3: Data exploration – Indiana Jones and the uncharted territories of data

Lecture 1: Data exploration overview. Why is it important/ What you will learn?

Lecture 2: Explore data through observation

Lecture 3: Explore data through interviews

Lecture 4: Explore data through reading

Lecture 5: Explore data through scientific articles

Lecture 6: Explore data through other sources

Lecture 7: Assignment #2: Become data explorer

Lecture 8: Remove duplicate information and name your variables

Lecture 9: Assignment #3: Bring the order

Lecture 10: Create a model for data analysis

Lecture 11: Assignment #4: Create your model

Chapter 4: Data collection – the poisonous triangle

Lecture 1: Data collection overview. Why is it important/ What you will learn?

Lecture 2: How to choose respondents?

Lecture 3: Choose the size of your sample

Lecture 4: Assignment #5: Define the sample size

Lecture 5: Create a survey – general guidelines

Lecture 6: Create a survey – choose type of questions

Lecture 7: Create a survey – choose type of variable measurement

Lecture 8: Create a survey – choose measurement scales

Lecture 9: Create a survey – write the actual survey

Lecture 10: Assignment #6: Create a survey

Lecture 11: Test your survey

Lecture 12: Assignment #7: Conduct test study

Lecture 13: Data collection methods

Lecture 14: Data collection – on-line method with Google Forms in detail

Lecture 15: Assignment #8: Take your Survey to Digital

Lecture 16: Promote your survey

Lecture 17: Assignment #9: Promotion time

Chapter 5: Data preparation – don't spoil the dish

Lecture 1: Data preparation overview. Why is it important/ What you will learn?

Lecture 2: Examine your dataset

Lecture 3: Remove unwanted data

Lecture 4: Identify and mark missing data

Lecture 5: Data formatting – five things to look out for

Lecture 6: Get rid of white spaces

Lecture 7: Correct typos

Lecture 8: Ensure consistent capitalization

Lecture 9: Change incompatible data units

Lecture 10: Assign the right data types

Lecture 11: Data transformation. Convert your data to meet the requirements

Lecture 12: Assignment #10: Clean and Transform

Chapter 6: Data analysis – cherry on top

Lecture 1: Data analysis overview. Why is it important/ What you will learn?

Lecture 2: What are descriptive statistics and how they work for data analysis?

Lecture 3: Data distribution. Is your data normal?

Lecture 4: Practical use of descriptive statistics

Lecture 5: Assignment #11: Calculate descriptive statistics

Lecture 6: What are inferential statistics and how they work for data analysis?

Lecture 7: Choose statistical software according to your data analysis method

Lecture 8: Download statistical software

Lecture 9: Assignment #12: Download SmartPLS 3 software

Lecture 10: Touring the interface

Lecture 11: Create a project and import data

Lecture 12: Assignment #13: Create your project and import data

Lecture 13: Create data groups

Lecture 14: Assignment #14: Create data groups for your project

Lecture 15: Create a model in the statistical software

Lecture 16: Assignment #15: Create a model for your project

Lecture 17: Time to analyze. Methods and procedures. What options do you have?

Lecture 18: Reliability of your results. Let’s talk about consistency

Lecture 19: Assignment #16: Check the reliability for your data analysis

Lecture 20: Validity of your results. Let’s talk about the truth

Lecture 21: Assignment #17: Check the validity for your data analysis

Lecture 22: Model Fit. How good is your model?

Lecture 23: Main results – the heart of your analysis

Lecture 24: Results for different groups. On the trail of diversity

Lecture 25: Mediation results. Looking for a middleman

Lecture 26: Export your data

Lecture 27: Results interpretation – main results for the general group

Lecture 28: Assignment #18: What your results mean – part 1

Lecture 29: Results interpretation – group analysis and mediation

Lecture 30: Assignment #19: What your results mean – part 2

Lecture 31: Optimize your future data analysis

Chapter 7: Data monetization – it’s all about the money

Lecture 1: Data monetization and usage overview. Why is it important/ What you will learn?

Instructors

Jacek Kułak
Digital Marketing Native

Rating Distribution

1 stars: 9 votes
2 stars: 24 votes
3 stars: 113 votes
4 stars: 228 votes
5 stars: 272 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu