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Mekhanik [1.2K]
1 year ago
15

Pressures of supply and demand act directly on the prices of airline tickets. As the seats available on the plane begin to fill,

airlines raise the price. If seats on a flight do not sell well, an airline may discount the tickets or even cancel the flight. Allie Henrich, a BYU-Idaho student, WANTED TO PREDICT THE PRICE OF TICKETS 14 DAYS BEFORE A FLIGHT BASED ON THE PRICE OF TICKETS LISTED 90 DAYS BEFORE THE SAME FLIGHT. For her study she compared the prices of one-way flights from London's Heathrow Airport to various destinations in Europe. Using Travelocity.com, she recorded the lowest published fares for 90 nonstop midweek flights 90 days in advance and then found the lowest published price for the same destination again 14 days in advance. The prices (in US dollars) are given in the file DirectFlightCosts. Notice that for some destinations, flights were not available.
1. Compute the sample correlation coefficient of the 14 Days before flight ticket prices compared with the 90-Days before flight ticket prices. Give your answer accurate to three decimals.2. Create a scatterplot using these two variables. Using this scatterplot and referring to the correlation coefficient above, select the answer that best describes the data illustrated in the scatterplot.a. Linear with a fairly strong negative associationb. Linear with a fairly strong positive associationc. Linear with a strong negative associationd. Nonlinear
Mathematics
1 answer:
aliina [53]1 year ago
8 0

Answer: 2

Step-by-step explanation:

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Compare and contrast XY with XY.
mojhsa [17]

Answer:

{}                                                                                                    XY                \overline {XY}

Represent a distance {}                                                                 √

Represent a segment {}                                                                                     √

Represent a numerical value {}                                                     √

Represent a geometric figure                                                                           √

Can be found by applying the ruler postulate  {}                         √

Can be be duplicated with a compass and a straight edge                          √

Step-by-step explanation:

The difference between XY and \overline {XY} are that the points XY represents the distance between two points having a numerical value whose value can be found by using a ruler to find difference in the numbers on the ruler that coincides with the points, while

4 0
2 years ago
If s(x) = x – 7 and t(x) = 4x2 – x + 3, which expression is equivalent to (t circle s) (x)?
Georgia [21]

Answer:

If s(x) = x – 7 and t(x) = 4x2 – x + 3, which expression is equivalent to (t*s)(x)? 4(x – 7)2 – x – 7 + 3 4(x – 7)2 – (x – 7) + 3 (4x2 – x + 3) – 7 (4x2 – x + 3)(x – 7)

8 0
2 years ago
Read 2 more answers
The lifespan (in days) of the common housefly is best modeled using a normal curve having mean 22 days and standard deviation 5.
Natasha_Volkova [10]

Answer:

Yes, it would be unusual.

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 normally distributed samples are solved using 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.

If Z \leq -2 or Z \geq 2, the outcome X is considered unusual.

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.

In this question, we have that:

\mu = 22, \sigma = 5, n = 25, s = \frac{5}{\sqrt{25}} = 1

Would it be unusual for this sample mean to be less than 19 days?

We have to find Z when X = 19. So

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

By the Central Limit Theorem

Z = \frac{19 - 22}{1}

Z = -3

Z = -3 \leq -2, so yes, the sample mean being less than 19 days would be considered an unusual outcome.

7 0
1 year ago
You ask 150 people about their pets. The results show that 9/25 of the people own a dog. Of the people who own a dog. 1/6 of the
pav-90 [236]

Answer: 9

Step-by-step explanation:

In order to find the people out of the 150, we first multiply 9/25 and 150 together. This will give us the people who DO own a dog. This brings us to 54.

Now, if we multiply 54 by 1/6 we get the answer of 9, because 1/6 of the dog owners own a cat as well. We have now reached the desired amount.

6 0
1 year ago
In a completely randomized experimental design involving three assembly methods, 30 employees were randomly selected and 10 were
AnnZ [28]

Answer:

F = \frac{MSR}{MSE} =\frac{45.89}{6.27}=7.32

So then the best option is:

a. 7.32

Step-by-step explanation:

Previous concepts

Analysis of variance (ANOVA) "is used to analyze the differences among group means in a sample".  

The sum of squares "is the sum of the square of variation, where variation is defined as the spread between each individual value and the grand mean"  

If we assume that we have 3 groups and on each group from j=1,\dots,10 we have 10 individuals on each group we can define the following formulas of variation:  

SS_{total}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x)^2  

SS_{between=Treatment}=SS_{model}=\sum_{j=1}^p n_j (\bar x_{j}-\bar x)^2  

SS_{within}=SS_{error}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x_j)^2  

And we have this property  

SST=SS_{between}+SS_{within}

Where SST represent the total sum of squares.  

The degrees of freedom for the numerator on this case is given by df_{num}=k-1=3-1=2 where k =3 represent the number of groups.  

The degrees of freedom for the denominator on this case is given by df_{den}=df_{between}=N-K=30-3=27.  

And the total degrees of freedom would be df=N-1=30 -1 =29  

From the info given we know that MSR=\frac{SSR}{2}=45.89

And MSE=\frac{SSE}{27}=6.27

From definition the F statisitc is defined as:

F = \frac{MSR}{MSE} =\frac{45.89}{6.27}=7.32

So then the best option is:

a. 7.32

3 0
2 years ago
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