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In a local election, 48,100 people voted. This was an increase of 7% over the last election. How many people voted in the last
2 answers:
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Answer:
Adrian's songs played on 9 commercials and 5 movies.
Step-by-step explanation:
Let x denotes number of commercials and y denotes number of movies.
Total number of commercials and movies = 14
So,
Adrian will earn $40 every time one of his songs is played in a commercial and he will earn $130 every time one of his songs is played in a movie
Total amount earned = $1010
Put in (ii)
Put in
Therefore, Adrian's songs played on 9 commercials and 5 movies.
Answer:
x = 4
Step-by-step explanation:
If you have any questions about the way I solved it, don't hesitate to ask me in the comments below
P.s: I used the Law of Sines, but there are many other ways to solve it
Given:
μ = 25 mpg, the population mean
σ = 2 mpg, the population standard deviation
If we select n samples for evaluation, we should calculate z-scores that are based on the standard error of the mean.
That is,
The random variable is x = 24 mpg.
Part (i): n = 1
σ/√n = 2
z = (24 -25)/2 = -0.5
From standard tables,
P(x < 24) = 0.3085
Part (ii): n = 4
σ/√n = 1
z = (24 -25)/1 = -1
P(x < 24) = 0.1587
Part (iii): n=16
σ/√n = 0.5
z = (24 - 25)/0.5 = -2
P(x < 24) = 0.0228
Explanation:
The larger the sample size, the smaller the standard deviation.
Therefore when n increases, we are getting a result which is closer to that of the true mean.
μ = 25 mpg, the population mean
σ = 2 mpg, the population standard deviation
If we select n samples for evaluation, we should calculate z-scores that are based on the standard error of the mean.
That is,
The random variable is x = 24 mpg.
Part (i): n = 1
σ/√n = 2
z = (24 -25)/2 = -0.5
From standard tables,
P(x < 24) = 0.3085
Part (ii): n = 4
σ/√n = 1
z = (24 -25)/1 = -1
P(x < 24) = 0.1587
Part (iii): n=16
σ/√n = 0.5
z = (24 - 25)/0.5 = -2
P(x < 24) = 0.0228
Explanation:
The larger the sample size, the smaller the standard deviation.
Therefore when n increases, we are getting a result which is closer to that of the true mean.