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Sergeeva-Olga [200]
3 years ago
10

In the pic thank you guys

Mathematics
1 answer:
Ahat [919]3 years ago
7 0

Answer:

The soda costs 2.20 and the sandwich costs 7.70

Step-by-step explanation:

To find this, set the soda cost as x. We now know that the sandwich cost is 3.5x. Add these together and set equal to 9.90

x + 3.5x = 9.90

4.5x = 9.90

x = 2.20

This is the cost of the soda. Now we can multiply that by 3.5 to get the sandwich cost.

3.5 * 2.20 = 7.70

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2x - 3y = -1<br> y = x - 1
Viktor [21]
Here’s how you would work it out

3 0
3 years ago
A sample size 25 is picked up at random from a population which is normally
Margarita [4]

Answer:

a) P(X < 99) = 0.2033.

b) P(98 < X < 100) = 0.4525

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 estabilishes 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.

Mean of 100 and variance of 36.

This means that \mu = 100, \sigma = \sqrt{36} = 6

Sample of 25:

This means that n = 25, s = \frac{6}{\sqrt{25}} = 1.2

(a) P(X<99)

This is the pvalue of Z when X = 99. So

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

By the Central Limit Theorem

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

Z = \frac{99 - 100}{1.2}

Z = -0.83

Z = -0.83 has a pvalue of 0.2033. So

P(X < 99) = 0.2033.

b) P(98 < X < 100)

This is the pvalue of Z when X = 100 subtracted by the pvalue of Z when X = 98. So

X = 100

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

Z = \frac{100 - 100}{1.2}

Z = 0

Z = 0 has a pvalue of 0.5

X = 98

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

Z = \frac{98 - 100}{1.2}

Z = -1.67

Z = -1.67 has a pvalue of 0.0475

0.5 - 0.0475 = 0.4525

So

P(98 < X < 100) = 0.4525

6 0
2 years ago
Simplify the expression -9+7
xenn [34]

We have

-9 + 7 = -2

You can also rewrite this as

7 - 9 = -2

If it makes you more comfortable.

Hope this helps.

7 0
3 years ago
Read 2 more answers
The following scatterplot shows the percentage of the vote a candidate received in the 2016 senatorial elections
neonofarm [45]

The critical values corresponding to a 0.01 significance level used to test the null hypothesis of ρs = 0 is (a) -0.881 and 0.881

<h3>How to determine the critical values corresponding to a 0.01 significance level?</h3>

The scatter plot of the election is added as an attachment

From the scatter plot, we have the following highlights

  • Number of paired observations, n = 8
  • Significance level = 0.01

Start by calculating the degrees of freedom (df) using

df =n - 2

Substitute the known values in the above equation

df = 8 - 2

Evaluate the difference

df = 6

Using the critical value table;

At a degree of freedom of 6 and significance level of 0.01, the critical value is

z = 0.834

From the list of given options, 0.834 is between  -0.881 and 0.881

Hence, the critical values corresponding to a 0.01 significance level used to test the null hypothesis of ρs = 0 is (a) -0.881 and 0.881

Read more about null hypothesis at

brainly.com/question/14016208

#SPJ1

3 0
1 year ago
(2x+3)+(5x17)+90=180
klasskru [66]

Answer:

x=10

Step-by-step explanation:

5 0
2 years ago
Read 2 more answers
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