bserved Frequencies: GENDER DRINK Male Female Total Tea 20 50 70 Coffee 10 40 50 Total 30 90 120 ill the below table of Expected Frequencies: GENDER DRINK Male Female Total Tea 70 Coffee 50 Total 30 90 120
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
![A social scientist wants to determine whether preference of tea or coffee is independent of gender. She randomly selects 120 people and gathered the data summarized in the table below.
Observed Frequencies:
GENDER
DRINK
Male
Female Total
Tea
20
50
70
Coffee
10
40
50
Total
30
90
120
Fill the below table of Expected Frequencies:
GENDER
DRINK
Male
Female
Total
Tea
70
Coffee
50
Total
30
90
120
Calculate the Chi-square test statistic:
What is the cut-off value if a = 0.01:
What is your conclusion:](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F14a30ae2-622b-412c-ba8c-2e78738508e1%2Fa0ad81fb-75a2-4a33-82d4-f934db50f9f9%2Fgq8u6q7_processed.png&w=3840&q=75)
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