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  • Choosing which statistical test to use.

  • There are many different tests you can use in statistics.

  • Sometimes it can be quite difficult to know which is the correct test to use.

  • This video will talk about seven tests you are likely to use.

  • involving means proportions and relationships.

  • When you are trying to work out which is the most appropriate test

  • there are three questions you should ask

  • One. What level of measurement was used for the data we are analyzing.

  • 2. How many samples do we have?

  • 3. What is the purpose of our analysis?

  • I will now explain each of these questions

  • 1. Data or level of measurement

  • Is our data nominal or interval/ratio?

  • Nominal data is also called categorical, qualitative

  • or nonparametric

  • Examples of nominal data are color

  • whether parts are defective or not,

  • or preferred type of chocolate.

  • Nominal summary values are usually stated as frequencies, proportions or

  • percentages.

  • The tests that involve nominal data are:

  • Test for a proportion

  • Difference of two proportions

  • and chi-squared test for independence

  • The other type of data

  • is interval/ratio

  • also called quantitative

  • Examples of interval/ratio data are

  • daily sales figures for choconutties

  • weight of peanuts or temperature

  • the most common summary value for interval/ratio data is a mean.

  • Tests that involve interval/ratio data are:

  • Test for a mean

  • difference of two means - independent samples

  • difference of two means - paired

  • and regression analysis.

  • For more help on levels of measurement see our video:

  • "Types of data nominal, ordinal, interval/ratio"

  • Ordinal data can be classified with nominal or interval/ratio

  • depending on the circumstances.

  • 2. Samples

  • Next we ask how many samples are involved

  • Is there one sample for which we are testing the relevant statistic

  • against a hypothesized value

  • or are there two samples

  • which are being compared with each other

  • or

  • is the one sample but each observation has a measure or score

  • for more than one variable?

  • The same sample is measured twice.

  • If we wish to compare a proportion or a mean against a given value,

  • this will involve one sample.

  • If we're comparing two different lots of people or things such as men and women

  • or people from two different departments

  • then we would have two samples.

  • If we have two sets of information on the same people of things

  • we would say we have one sample with two variables.

  • An example is one set of days and information on how many choconutties

  • are sold and what the temperature was.

  • Or - one set of people and information on their gender and preferred type of chocolate.

  • Finally we ask

  • What is the purpose of the analysis?

  • We can be testing against the hypothesized value

  • comparing two statistics

  • or looking for a relationship.

  • Chi-squared test for independence and regression are similar

  • in that they are looking at the relationship between two variables

  • The difference between them is in the kind of data.

  • If you would summarize the data in s table,

  • we would use a chi-squared test fo independence

  • whereas if you would put it on a scatter plot

  • you would use regression analysis.

  • Here iss an example for each of these tests.

  • They relate back or out other videos teaching about hypothesis testing.

  • After each description of the scenario pause the video

  • and see if you can identify the correct test before we tell you the answer.

  • Helen is still selling choconutties.

  • Example one:

  • sufficient nuts.

  • Helen was concerned whether the quantity of nuts was sufficient in her choconutties.

  • She took a sample of twenty packets and found the weight of nuts in

  • each packet

  • Pause the video

  • 1. Data

  • The weight was interval/ratio data.

  • 2. Samples

  • There was just one sample of twenty packets of choconutties.

  • 3. Purpose. Helen was comparing against given value

  • Thus, the test she needs to use is Test for a mean.

  • Example Two

  • Prize tickets

  • In a promotional campaign twenty percent of all packs of choconutties should

  • include tickets for free prizes.

  • Helen takes a sample of fifty packets and finds that seven of them

  • have winning tickets

  • Pause the video

  • 1. Data: For each bar we are saying yes or no, only to be lumped whether or not

  • there is a ticket.

  • This is nominal data from which we get a sample proportion of seven out of fifty

  • Or 0.14

  • Samples

  • There is one sample of fifty packets

  • Purpose.

  • Helen is comparing the sample value against a given value: twenty percent

  • We conclude that the test she needs to use is test for a proportion.

  • Example three

  • Bar longevity compared with nuttabars.

  • Helen thinks her choconutties last longer than the competition, nuttabars.

  • She gets 36 people to eat one of each, and records their eating times.

  • Pause now

  • 1. Data. Helen collects times taken in seconds

  • so this is interval/ratio data.

  • 2. Samples

  • There is one sample of thirty-six people but with two scores for each person

  • the time for the choconuttie and the time for the nuttabar.

  • 3. Purpose

  • She is looking at whether there iss a difference in the amount of time taken

  • for each of the bars.

  • Thus the test is difference of two means, paired sample.

  • Example four

  • Defective wrapping from two wrapping machines

  • Helen thinks there is a difference in performance between

  • the two wrapping machines in her factory. She checks 200 bars from

  • one machine and 150 bars from the other.

  • For each bar she is seeing if the wrapping is satisfactory or not

  • She finds that ten out of two hundred bars from the first machine

  • and nine out of 150 bars from the second machine

  • are badly wrapped.

  • Pause the video

  • Data. The information for each bar is OK or not ok

  • This is nominal data.

  • It has been summarized as frequencies.

  • 2. Samples there are two independent samples

  • one sample from each of the two machines

  • 3. Purpose

  • Helen is comparing the proportions from the two samples

  • We can see that the test is

  • difference of two proportions.

  • Example five

  • Do stickers help sales?

  • Helen is exploring whether having free stickers makes a difference to sales.

  • She has the sales figures for thirteen days when she did offer free stickers

  • and ten days when she did not. Pause and decide on the test

  • Data. For each day Helen has a number or value corresponding to the sales for that day

  • This is interval/ratio data

  • It is summarized as a mean member of sales.

  • 2. Samples

  • There are two samples one sample for days with stickers

  • and one sample for days without.

  • 3. Purpose

  • Helen is comparing the average sales figures for the two treatments

  • we conclude that the test to use is...

  • Difference of two means independent samples

  • Example six

  • Are sales affected by temperature?

  • Helen wants to see if there is a relationship between the daily

  • temperature and sales of choconutties.

  • She has data on sales and temperature

  • for thirty weekdays of sales

  • Pause!

  • Data. Sales and temperature at both interval variables

  • Samples

  • There is one sample of thirty days with two measures or scores for each day.

  • Purpose.

  • Helen is interested in the relationship between sales and temperature

  • This leads us to decide that the test is regression.

  • Example seven

  • Men and women and chocolate preference

  • Helen is thinking of selling dark chocolate, milk chocolate and white chocolate

  • choconutties.

  • She thinks that men and women might have different preferences with regard to type.

  • She collects data from fifty customers, noting down if they are men or women

  • and asking them which variety they prefer.

  • Pause the video and decide.

  • Data. Helen records the type of chocolate and sex of person.

  • These are both nominal variables.

  • Samples.

  • There is one sample of fifty customers

  • but with two measures or variables.

  • Purpose.

  • Helen is looking at whether there is a relationship

  • variables

  • Thus the test is chi-squared test for independence.

  • Those are seven examples of the seven tests outlined here.

  • There are numerous other statistical tests and other things may need to be

  • considered,

  • but this summary will help you to understand what these seven basic tests do

  • and what to look for when deciding on which test to choose.

Choosing which statistical test to use.

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Choosing which statistical test to use - statistics help.

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    Zhenyu posted on 2020/03/25
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