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Olin [163]
2 years ago
8

A set of cards contains cards numbered 1 – 8. Mrs. Jacob’s class is conducting an experiment in which a card is drawn from the p

ile, the number is recorded, and then the card is returned to the set. The class will conduct 1,000 trials. Based on the theoretical probability, which is the best prediction for the number of times a 4 will be drawn from the pile? 111 125 143 250
Mathematics
1 answer:
Alchen [17]2 years ago
7 0

Answer:

The best prediction for the number of times a 4 will be drawn from the pile is:

                       125

Step-by-step explanation:

It is given that:

A set of cards contains cards numbered 1 – 8.

So, the theoretical probability that 4 comes up is:

Ratio of Number of favorable outcome( outcome of 4) to the total umber outcome(i.e. 8 )

Hence, Theoretical Probability that 4 is drawn=1/8

Now, out of 1000 trials the best prediction of number of times 4 is drawn is:

(The probability of drawing 4)×(Number of experiments or trials)  

=(1/8)×1000

=125

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Histogram or Bar Chart? Select which graphical display is most appropriate to describe the distribution for each of the variable
lara31 [8.8K]

Answer:

a) Bar chart

b) Histogram

c) Bar chart

d) Histogram

Step-by-step explanation:

a) Trash pick-up DAY for each HOUSEHOLD in Ames - This is categorical data because, we are talking about days of the week. For instance, Household 1 might have Sunday as Trash pick-up day and that could be accumulated into frequency. Hence, BAR chart is the most appropriate.

b) Patient WAIT-TIME at ISU. This is continuous (quantitative) data. And the most appropriate is HISTOGRAM.

c) Number of trips taken during a GIVEN SCHOOL YEAR by EACH ISU STUDENT. Let say we have 5 ISU STUDENTS. Student 1 had 5 trips, student 2 had 10 trips, etc.

We want to see which student has the most and least trip in that particular school year. Although is count data but the most appropriate graphical display is BAR chart.

d) TAX BRACKET of ALL Iowa RESIDENTS. This is a continuous (quantitative) data. The most appropriate graphical display is HISTOGRAM.

5 0
3 years ago
The mean per capita income is 16,127 dollars per annum with a variance of 682,276. What is the probability that the sample mean
MakcuM [25]

Answer:

0.60% probability that the sample mean would differ from the true mean by more than 104 dollars if a sample of 476 persons is randomly selected

Step-by-step explanation:

To solve this question, we have to understand the normal probability distribution and the central limit theorem.

Normal probability distribution:

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean \mu and standard deviation \sigma, a large sample size can be approximated to a normal distribution with mean \mu and standard deviation, which is also called standard error s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

The standard deviation is the square root of the variance. So

\mu = 16127, \sigma = \sqrt{682276} = 826, n = 476, s = \frac{826}{\sqrt{476}} = 37.86

What is the probability that the sample mean would differ from the true mean by more than 104 dollars if a sample of 476 persons is randomly selected

Either it differs by 104 or less dollars, or it differs by more than 104 dollars. The sum of the probabilities of these events is 100. I am going to find the probability that it differs by 104 or less dollars first.

Probability that it differs by 104 or less dollars first.

pvalue of Z when X = 16127 + 104 = 16231 subtracted by the pvalue of Z when X = 16127 - 104 = 16023. So

X = 16231

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{16231 - 16127}{37.86}

Z = 2.75

Z = 2.75 has a pvalue of 0.9970

X = 16023

Z = \frac{X - \mu}{s}

Z = \frac{16023 - 16127}{37.86}

Z = -2.75

Z = -2.75 has a pvalue of 0.0030

0.9970 - 0.0030 = 0.9940

99.40% probability that it differs by 104 or less.

What is the probability that the sample mean would differ from the true mean by more than 104 dollars if a sample of 476 persons is randomly selected

p + 99.40 = 100

p = 0.60

0.60% probability that the sample mean would differ from the true mean by more than 104 dollars if a sample of 476 persons is randomly selected

7 0
3 years ago
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