The experimental probability of getting heads can be calculated by subtracting the number of tails from the total number of tosses, then dividing by the total number of tosses.
Total number of tosses = 50
Number of tails = 14
Number of heads = 50 - 14 = 36
Experimental probability of getting heads = Number of heads / Total number of tosses
Experimental probability of getting heads = 36 / 50 = 0.72
Therefore, the experimental probability of getting heads is 72%.
You toss a coin 50 times and get 14 tails. What is the experimental probability of getting heads?(1 point)
Responses
28%
7/25
72%
0.36
11 answers
Bob spun a spinner with 6 equal sections 150 times and recorded the results. What is the experimental probability of landing on green?
colors where the spinner stopped frequency
blue 20
red 15
green 45
yellow 10
black 15
white 45
total 150
(1 point)
Responses
45%
45%
30%
30%
3%
3%
0.45%
colors where the spinner stopped frequency
blue 20
red 15
green 45
yellow 10
black 15
white 45
total 150
(1 point)
Responses
45%
45%
30%
30%
3%
3%
0.45%
To calculate the experimental probability of landing on green, we first need to determine the frequency of landing on green out of the total number of spins:
Frequency of landing on green = 45
Total number of spins = 150
Experimental probability of landing on green = Frequency of landing on green / Total number of spins
Experimental probability of landing on green = 45 / 150 = 0.3
So, the experimental probability of landing on green is 30%.
Frequency of landing on green = 45
Total number of spins = 150
Experimental probability of landing on green = Frequency of landing on green / Total number of spins
Experimental probability of landing on green = 45 / 150 = 0.3
So, the experimental probability of landing on green is 30%.
A calculator manufacturing company checks 500 calculator units and finds that 25 of them have non-functioning keys. What is the relative frequency of a non-defective calculator from this batch of items?(1 point)
Responses
475500
475 over 500
1920
19 over 20
120
1 over 20
25500
25 over 500
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Responses
475500
475 over 500
1920
19 over 20
120
1 over 20
25500
25 over 500
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To calculate the relative frequency of a non-defective calculator from this batch of items, we need to subtract the number of defective calculators from the total number of calculators, then divide by the total number of calculators.
Number of non-defective calculators = Total number of calculators - Number of defective calculators
Number of non-defective calculators = 500 - 25 = 475
Relative frequency of non-defective calculators = Number of non-defective calculators / Total number of calculators
Relative frequency of non-defective calculators = 475 / 500 = 0.95
So, the relative frequency of a non-defective calculator from this batch of items is 95% or 19 over 20.
Number of non-defective calculators = Total number of calculators - Number of defective calculators
Number of non-defective calculators = 500 - 25 = 475
Relative frequency of non-defective calculators = Number of non-defective calculators / Total number of calculators
Relative frequency of non-defective calculators = 475 / 500 = 0.95
So, the relative frequency of a non-defective calculator from this batch of items is 95% or 19 over 20.
A quality controller inspected 1,000 units of a product and rejected 150 units due to defects. Find the experimental probability that a unit will pass inspection.(1 point)
Responses
320
3 over 20
0.15%
0 point 1 5 percent
1720
17 over 20
15%
Responses
320
3 over 20
0.15%
0 point 1 5 percent
1720
17 over 20
15%
To find the experimental probability that a unit will pass inspection, we need to subtract the number of rejected units from the total units inspected and then divide by the total units inspected.
Number of units passing inspection = Total units inspected - Number of rejected units
Number of units passing inspection = 1000 - 150 = 850
Experimental probability that a unit will pass inspection = Number of units passing inspection / Total units inspected
Experimental probability that a unit will pass inspection = 850 / 1000 = 0.85 or 85%
So, the experimental probability that a unit will pass inspection is 85%.
Number of units passing inspection = Total units inspected - Number of rejected units
Number of units passing inspection = 1000 - 150 = 850
Experimental probability that a unit will pass inspection = Number of units passing inspection / Total units inspected
Experimental probability that a unit will pass inspection = 850 / 1000 = 0.85 or 85%
So, the experimental probability that a unit will pass inspection is 85%.
choose one of the answer choices
0.85 or 85%
In which scenario is the theoretical probability equal to the experimental probability?(1 point)
Responses
A coin is flipped six times and heads appears each time
A coin is flipped six times and heads appears each time
A number cube is rolled six times and an even number appears each time
A number cube is rolled six times and an even number appears each time
A number cube is rolled six times and a 6 appears four times
A number cube is rolled six times and a 6 appears four times
A coin is flipped six times and heads appears three times
Responses
A coin is flipped six times and heads appears each time
A coin is flipped six times and heads appears each time
A number cube is rolled six times and an even number appears each time
A number cube is rolled six times and an even number appears each time
A number cube is rolled six times and a 6 appears four times
A number cube is rolled six times and a 6 appears four times
A coin is flipped six times and heads appears three times
A number cube is rolled six times and an even number appears each time