Probability and Contingency tables

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In summary, there are more than two people who meet the conditions to receive a free tablet computer from their employer.
  • #1
gooses34
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Here is my question from table chart below as i ma getting a little confused with the AND/OR

Question: Of getting someone who would want his/her employer to offer free use of a tablet computer AND someone who works in the manufacturing sector?

Smart phoneWireless business projectorTablet computerTotal
Workers in manufacturing sector1685132921275141
Workers in the service industry1235227211164623
Total2920360132439764
 
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  • #2
Hi goose34,

Welcome to MHB! :)

I think the question you are asking is what is the probability of someone using a tablet computer and working in the manufacturing sector? Is that correct?

How many people fit both conditions? How many people could possibly fit both?
 
  • #3
Well its a quiz and this is what it says

We- Compute magazine did a survey of 9764 working people. They were asked these two questions.A. Do you work in the manufacturing sector or service industry?
B. If your employer were to offer you free use of one type of smart technology, which one would be most helpful to you at your job?The responses were put into the table you fixed for me.

And the question was

8) Of getting someone who would want his/her employer to offer free use of a tablet computer AND someone who works in the manufacturing sector... thought it was 2127/9764

9) Of getting someone who would want his/her employer to offer free use of a tablet computer OR someone who works in the manufacturing sector? ... I thought it was 1116+5142/9764

Thanks
 
  • #4
If this is a current quiz you are taking for credit, than we can't help you. I'm sorry but unless we know that your teacher is ok with you receiving outside help then from our point of view we might be helping you cheat. If you are allowed to get help or this is for a past quiz or something, please let me know.

Please let me know what the situation is. While you think it over, this website might be helpful. It provides some examples of using contingency tables and probabilities.
 
  • #5
Well it's not really a quiz its a question that i didn't understand that's all
 
  • #6
Your calculation for the "and" condition is correct. It must match both criteria and we divide by the total.

For "or", the phrasing of the question is a bit unclear but it must meet either condition in order to be counted. Which cells meet at least one of those conditions? There are more than two. Anyone who works in the manufacturing industry or wants a tablet qualifies. We can count this a couple of ways but let's start with this.
 

FAQ: Probability and Contingency tables

What is a contingency table?

A contingency table is a type of data representation that displays the frequency of different categories or variables in a dataset. It is used to analyze the relationship between two or more categorical variables.

How is probability related to contingency tables?

Probability is used in contingency tables to calculate the likelihood of an event occurring based on the frequency of its occurrence in a dataset. It helps to determine the probability of one variable occurring given another variable's occurrence.

What is the purpose of creating a contingency table?

The main purpose of creating a contingency table is to analyze the relationship between two or more categorical variables. It helps to identify patterns and trends in the data and make comparisons between different groups or categories.

How are contingency tables used in statistical analysis?

Contingency tables are used in statistical analysis to perform tests such as chi-square tests, which help to determine if there is a significant relationship between two categorical variables. They are also useful in calculating measures of association, such as the Phi coefficient and Cramer's V, to quantify the strength of the relationship between variables.

What are the limitations of using contingency tables?

Contingency tables have certain limitations, such as only being able to analyze categorical data and not being able to determine cause and effect relationships. They also assume that the variables being analyzed are independent of each other, which may not always be the case. Additionally, contingency tables may become overly complex and difficult to interpret when dealing with large datasets or a large number of variables.

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