Justin wants to place one of his 4 signed hockey sticks on his shelf. The length of the shelf is exactly 1.05 meters. His 4 hock
1 answer:
Answer:
Stick 2
Step-by-step explanation:
Given
--- Shelf length
<u>Missing information from the question are:</u>
<em>See attachment</em>
Required
Which stick best fits the shelf?
The following observations are to be noted:
- The length of stick 1 of 1.4m is greater than the length of the shelf
- The length of stick 3 of 1.14m is greater than the length of the shelf
- The length of stick 4 of 1.104m is greater than the length of the shelf
- <em>Only stick 2 (of length 1.041m) has a smaller length when compared to the length of the shelf.</em>
<em />
<em>Hence, Justin should choose stick 2</em>
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Answer:
The z-score for this data is Z = -0.26.
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 and standard deviation
, the z-score of a measure X is given by:
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 and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
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 and standard deviation
This is based on knowledge that in the U.S., the mean PAL is 1.65 and the standard deviation is 0.55.
This means that
A study took a random sample of 51 people who lived in low income neighborhoods and found their mean PAL to be 1.63.
This means that
Using a one-sample z test, what is the z-score for this data
By the Central Limit Theorem
The z-score for this data is Z = -0.26.