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vodomira [7]
3 years ago
14

How do I solve this I’m dumb

Mathematics
1 answer:
laila [671]3 years ago
8 0
-1/4 + f/8 = 1/2.
The LCD is 8.  Rewrite this equation as    -8/4 + 8f/8 = 8(1/2) and then reduce the result:

-2 + f = =4

Then f = 6.

You should check this result.

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There can be more than one option answer fast in two minutes
olasank [31]

Answer:

QR and SV

RS and TU

Step-by-step explanation:

3 0
3 years ago
it is known that the population proton of utha residnet that are members of the church of jesus christ 0l6 suppose a random samp
Lady_Fox [76]

Answer:

0.0838 = 8.38% probability of obtaining a sample proportion less than 0.5.

Step-by-step explanation:

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

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

Proportion of 0.6

This means that p = 0.6

Sample of 46

This means that n = 46

Mean and standard deviation:

\mu = p = 0.6

s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.6*0.4}{46}} = 0.0722

Probability of obtaining a sample proportion less than 0.5.

p-value of Z when X = 0.5. So

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

By the Central Limit Theorem

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

Z = \frac{0.5 - 0.6}{0.0722}

Z = -1.38

Z = -1.38 has a p-value of 0.0838

0.0838 = 8.38% probability of obtaining a sample proportion less than 0.5.

8 0
3 years ago
What is th e best estimate for 5 1/9 - 1 5/6
valentinak56 [21]
5 1/9 - 5 5/6 is 3.27, if you want it rounded to the nearest whole number then that would by 3

have a nice day :)
3 0
4 years ago
A store buys 17 sweaters for $204 and sells them for $646. how much profit does the store make per sweater?
uranmaximum [27]

Total profit: 646 - 204 = 442


profit per shirt = 442 / 17 = 26


Answer: $26

6 0
2 years ago
I need help with this question can someone please help me?
zlopas [31]
Answer: y= -1/1x - 1

Okay, to find the equation you must find the y-intercept and the slope.

To find the y-intercept, you must find (0,y). This is the point on the y-axis where x is 0. So, where along the y-axis is there a point? There is a point at (0,-1). Therefore, your y-intercept is -1.

To find the slope, you must do rise/run. Go to a point on the line, such as (0,-1). You must go up (or down) until you get lined up with next point on the line. You go up one time. Then, you must go right (or left) to get to the exact point. In this case, the point would be (-1,0). You go left one time.

If you go down or left when doing rise/run, the number would be negative. Since you went left, that number would be negative.

So, our slope would be 1/-1, which can also be written as -1/1.

Now, write the equation. There is always an x next to the slope. y= -1/1x

Then, put the y-intercept next to it. If it is positive, use a +. If it is negative, use a -. It is negative.

Therefore, the answer is y= -1/1x -1.
5 0
3 years ago
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