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Course Content
01 Introduction – the adventure begins
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001 Introduction
02:34
02 Data planning – its like a bank robbery
0/9
002 Data planning overview. Why it is important What you will learn
01:09
003 Where to start
04:57
004 What was first the chicken or the egg
01:16
005 Two types of data
02:20
006 Choose data analysis method
04:34
007 How to find data
01:30
008 Option 1 Find data already collected by someone else
04:01
009 Option 2 Order collection of data to the research company
07:13
010 Option 3 Collect data by yourself
01:11
03 Data exploration – Indiana Jones and the uncharted territories of data
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011 Data exploration overview. Why is it important What you will learn
01:22
012 Explore data through observation
01:54
013 Explore data through interviews
02:57
014 Explore data through reading
03:12
015 Explore data through scientific articles
06:01
016 Explore data through other sources
02:13
017 Assignment 2 Become data explorer
018 Remove duplicate information and name your variables
04:25
019 Assignment 3 Bring the order
020 Create a model for data analysis
01:53
021 Assignment 4 Create your model
04 Data collection – the poisonous triangle
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022 Data collection overview. Why is it important What you will learn
02:28
023 How to choose respondents
06:04
024 Choose the size of your sample
04:39
025 Assignment 5 Define the sample size
026 Create a survey – general guidelines
05:49
027 Create a survey – choose type of questions
02:21
028 Create a survey – choose type of variable measurement
03:45
029 Create a survey – choose measurement scales
06:31
030 Create a survey – write the actual survey
14:40
031 Assignment 6 Create a survey
032 Test your survey
02:30
033 Assignment 7 Conduct test study
034 Data collection methods
03:53
035 Data collection on-line method with Google Forms in detail
19:24
036 Assignment 8 Take your Survey to Digital
037 Promote your survey
02:46
038 Assignment 9 Promotion time
05 Data preparation – dont spoil the dish
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039 Data preparation overview. Why is it important What you will learn
03:32
040 Examine your dataset
03:33
041 Remove unwanted data
06:49
042 Identify and mark missing data
07:09
043 Data formatting – five things to look out for
03:21
044 Get rid of white spaces
03:39
045 Correct typos
06:24
046 Ensure consistent capitalization
04:03
047 Change incompatible data units
06:28
048 Assign the right data types
05:35
049 Data transformation. Convert your data to meet the requirements
21:47
050 Assignment 10 Clean and Transform
06 Data Analysis cherry on top
0/30
051 Data analysis overview. Why is it important What you will learn
02:35
052 What are descriptive statistics and how they work for data analysis
09:35
053 Data distribution. Is your data normal
10:33
054 Practical use of descriptive statistics
22:27
055 Assignment 11 Calculate descriptive statistics
056 What are inferential statistics and how they work for data analysis
10:35
057 Choose statistical software according to your data analysis method
04:04
058 Download statistical software
05:56
060 Touring the interface
11:27
061 Create a project and import data
03:30
062 Assignment 13 Create your project and import data
063 Create data groups
05:18
064 Assignment 14 Create data groups for your project
065 Create a model in tache statistical software
06:30
066 Assignment 15 Create a model for your project
067 Time to analyze. Methods and procedures. What options do you have
05:56
068 Reliability of your results. Lets talk about consistency
07:10
069 Assignment 16 Check the reliability for your data analysis
070 Validity of your results. Lets talk about the truth
06:35
071 Assignment 17 Check the validity for your data analysis
072 Model Fit. How good is your model
02:08
073 Main results – the heart of your analysis
09:38
074 Results for different groups. On the trail of diversity
10:32
075 Mediation results. Looking for a middleman
09:26
076 Export your data
03:05
077 Results interpretation – main results for the general group
22:11
078 Assignment 18 What your results mean – part 1
079 Results interpretation – group analysis and mediation
06:29
080 Assignment 19 What your results mean – part 2
081 Optimize your future data analysis
05:30
07 Data monetization – its all about the money
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082 Data monetization and usage overview. Why is it important What you will learn
02:02
083 Connotations-of-colors
07:31
08 Conclusion and next steps – there is no finish line
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090 Conclusion
03:09
09 Bonus – theres always more
0/3
091 How the bonus section will be developed
00:36
092 Formative measurement analysis
06:15
093 Effect size f square – are my results meaningful
03:01
Data Analysis & Statistics practical course for beginners
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