44. Skiing A skier is trying to decide whether or not to buy a

1 answer:

5 0

$67 x 6 = 402
402 + (25 x 6) = 552

$350 + (25 x 6) = 500

the skier would have to go skiing for 6 days in order to make the season pass less expensive than the daily pass.

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Frank has a jar filled with 200 old dimes. Suppose he selects a dime from the jar without looking. There is a 20% chance that he

a_sh-v [17]

Answer: 40

Step-by-step explanation:

Given

Jar contains 200 old dimes

Chances to pick the 1960s is 20% i.e. 1960s is 20% of 200 old dimes

So, we can write

$\Rightarrow \text{No of 1960s is }=20\%\ \text{of}\ 200=0.2\times 200\\\Rightarrow \text{No of 1960s is }=40$

8 0

3 years ago

Could someone please answer this who actually knows how to do it please??!

posledela

Answer:

x+y= 59, x-y= -13

Step-by-step explanation:

We know that x is the smaller number and y is the bigger number. We also know that the difference is 13, meaning x-y= -13. Since the sum of the two numbers is 59, x+y= 59

8 0

3 years ago

Read 2 more answers

A researcher reports survey results by stating that the standard error of the mean is 25 the population standard deviation is 40

bezimeni [28]

Answer:

a) A sample of 256 was used in this survey.

b) 45.14% probability that the point estimate was within ±15 of the population mean

Step-by-step explanation:

This question is solved using the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use 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 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 $s = \frac{\sigma}{\sqrt{n}}$ .