Data Analysis Flashcards
What are some types of data
Quantitative
Qualitative
Discrete
Continuous
What is the internet of things (IoT)
Internet devices are connected and continually collecting data which can be used
What does ACCURATE stand for in regard to determining the quality of good informatio
Accurate Complete Cost-beneficial User-targeted Relevant Authoritative Timely Easy to use
What is an inferential analysis
When a random sample of data is taken from a population and is used to make inferences about the whole population
What is exploratory data analysis
Analysing data using patterns such as regressions and correlations
What is confirmatory data analysis
Using hypothesis tests to reject a null hypothesis
What are the three main reasons we use sampling instead of the whole population
Whole population may not be known
Testing the whole population may be impossible
Items may be destroyed upon testing
What are some examples of bias
Selection bias - sample items are not uniformly picked
Self-selection bias - including/discluding yourself
Observer bias - observer’s prejudices
Omitted variables bias - variables left out
Cognitive bias - how data is perceived
Confirmation bias - confirming what you previously believe
Survivorship bias - ignore those that have failed
What are type I and type II errors
Type I: False positive
Type II: False negative
What are the four Vs of big data
Volume
Variety
Velocity
Veracity
What are some of the benefits of big data
Decision making
Customer analysis
Innovation
Risk management
What are some risks of big data
Inadequate storage Lack of skilled workers Data dependency Overload of information Data privacy and security
