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Data Presentation, Analysis and Interpretation Flashcards | StudBud
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Data Presentation, Analysis and Interpretation
Data Presentation, Analysis and Interpretation
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Answers
1
A confidence interval tells you the exact value of a population parameter
True
False
2
Inferential statistics allow you to estimate population parameters from samples
True
False
3
What are some of the challenges of data analysis?
Data can be messy and incomplete
Choosing the right statistical methods can be difficult
All of the above
Data collection can be time consumig and expensive
4
Data analysis is only used in scientific research
True
False
5
Data analysis is a valuable skill for many different careers
True
False
6
A larger sample size will generally result in a wider confidence interval.
True
False
7
What is the difference between nominal and ordinal data?
Ordinal data is measured in years, while nominal data is measured in months
Nominal data can be ranked, while ordinal data cannot
Ordinal data can be ranked, while nominal data cannot
There is no difference between nominal or ordinal data
8
What is the first step in data analysis?
Collecting data
Cleaning data
Identifying the problem
Analyzing data
9
What is an outlier in data analysis?
A data point that is outside the confidence interval
A data point that is missing
A data point that is formatted incorrectly
A data point that is significantly different from the rest of the data
10
There is always a right answer in data analysis
True
False
11
What is the purpose of data cleaning?
To calculate summary statistics
To identify outliers and inconsistencies in the data
To format the data for presentation
To test hypotheses about the data
12
What skills are important for data analysis?
All the above
Problem solving skills
Data visualization skills
Critical thinking
13
What is the significance level in hypothesis testing?
Probability of making correct decision when alternative hypothesis is true
Probability of observing the data we did if the null hypothesis were true
The probability of the null hypothesis being true
Probability of making the wrong decision when the null hypothesis is true
14
What is the difference between descriptive and inferential statistics?
Inferential describe data, descriptive allow you to make inferences
Descriptive describe data, inferential allow you to make inferences.
Descriptive used for quantitative, inferential used for qualitative
There is no difference
15
The mean, median, and mode are all examples of descriptive statistics
True
False
16
What are some of the benefits of using data analysis?
All of the above
Improved decision making
Communication of complext information
Identification of patterns and trends
17
When choosing a chart for data presentation, it is important to consider the type of data you are presenting
False
True
18
It is always necessary to remove outliers from your data set.
False
True
19
Data presentation is the same as data analysis
True
False
20
What are some common types of charts used in data presentation?
Bar charts, pie charts, line charts
Tables, spreadsheets, graphs
Text documents, emails, presentations
Images, videos, audio recordings
