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What are the steps of statistical investigation?
Defining the problem 2.gathering relevant information 3. presenting/organizing data 4.analyzing data 5. interpreting results
3 ways of presenting data in statistics?
ways of presenting data in statistics
What are ways of presenting experimental data?
wat are the two ways of presenting experimental data
What are the methods of presenting data?
two methods of presenting data 1.tabular form 2.pictorial form
Give ways of presenting data collected?
give 2 ways of presenting data
What are the steps of statistical investigation?
Defining the problem 2.gathering relevant information 3. presenting/organizing data 4.analyzing data 5. interpreting results
Why are graphs important when organizing data?
A graph is a visual aid on which data may be seen and understood.
Why is organizing research data important?
To know the answer to what you are asking.
Is organizing data important for sharing result of an experiment with other s?
Yes
What mistake should be avoided when presenting an argument and why are these important in developing effective arguments?
Incorrect data. It is not important to have incorrect data, in fact quite the opposite.
Why are graphs important in statistics?
Graphs visualize data allowing the brain to interpret a large data set quickly and infer trends.
3 ways of presenting data in statistics?
ways of presenting data in statistics
What are the ways of presenting data?
Chart And Graph... :D
What do you understand by organizing data?
putting data in a specific place/order is called organizing data.
What are ways of presenting experimental data?
wat are the two ways of presenting experimental data
What are the steps of a typical statistical investigation?
The first step is to define the problem. The second step is gathering relevant information. The third step is presenting/organizing data. The fourth step is to analyze the data. The fifth step is to interpret the results.
What do you understand by organizing?
putting data in a specific place/order is called organizing data.
