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Rashid [163]
1 year ago
12

Elijah and Jonathan play on the same soccer team. They have played 3 of their 15,

Mathematics
1 answer:
Lynna [10]1 year ago
5 0

Answer:

Only Elijah's model is correct

Step-by-step explanation:

The data given in the question tells us they have 12 games left on their soccer team. Each one of them tried to simulate the fact by creating some model which look like a balance between quantities.

Elijah placed 3 cubes of value 1 and a cube of value x on one side of a balance. On the other side, he placed 15 cubes of value 1. He was obviously modeling the fact that 15 cubes (games due to play in our case) should be equal to 3 cubes (games already played) plus the x numbers left to play

This model if perfect, since the only way to equilibrate the balance is setting x to 12, the games left to play

Jonathan used a table with 3 x's in a row and a 15 in the second row, trying to model the same situation. To our interpretation, this table doesn't show the number of games left to play. If we equate 3x = 15, we get x=5 which has nothing to do with the situation explained in the question, so this model is not correct.

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A cargo ship left port A and is headed across the ocean to shipping port B. After one month, the ship stopped at a refueling sta
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Answer:

D

Step-by-step explanation:

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8 0
2 years ago
Read 2 more answers
Last year, 46% of business owners gave a holiday gift to their employees. A survey of business owners indicated that 35% plan to
DiKsa [7]

Answer:

a) Number = 60 *0.35=21

b) Since is a left tailed test the p value would be:  

p_v =P(Z  

c) If we compare the p value obtained and using the significance level given \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% the proportion of business owners providing holiday gifts had decreased from the 2008 level.  

We can use as smallest significance level 0.044 and we got the same conclusion.  

Step-by-step explanation:

Data given and notation  

n=60 represent the random sample taken

X represent the business owners plan to provide a holiday gift to their employees

\hat p=0.35 estimated proportion of business owners plan to provide a holiday gift to their employees

p_o=0.46 is the value that we want to test

\alpha=0.05 represent the significance level

Confidence=95% or 0.95

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

Part a

On this case w ejust need to multiply the value of th sample size by the proportion given like this:

Number = 60 *0.35=21

2) Part b

We need to conduct a hypothesis in order to test the claim that the proportion of business owners providing holiday gifts had decreased from the 2008 level:  

Null hypothesis:p\geq 0.46  

Alternative hypothesis:p < 0.46  

When we conduct a proportion test we need to use the z statisitc, and the is given by:  

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

Calculate the statistic  

Since we have all the info requires we can replace in formula (1) like this:  

z=\frac{0.35 -0.46}{\sqrt{\frac{0.46(1-0.46)}{60}}}=-1.710  

Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The significance level provided \alpha=0.05. The next step would be calculate the p value for this test.  

Since is a left tailed test the p value would be:  

p_v =P(Z  

Part c

If we compare the p value obtained and using the significance level given \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% the proportion of business owners providing holiday gifts had decreased from the 2008 level.  

We can use as smallest significance level 0.044 and we got the same conclusion.  

8 0
2 years ago
Corinne and Aretha are having a 26-mile race. Corinne gave Aretha a head start by letting her begin 3.5 miles in front of the st
Ronch [10]
From the table, the speed of Corinne is given by

speed=slope= \frac{2.5-1.25}{20-10} = \frac{1.25}{10} =0.125 \ miles / minute

From the graph, the speed of Aretha is given by

speed=slope= \frac{5.5-4.5}{20-10} = \frac{1}{10} =0.1 \ miles / minute

The distance from the starting point of Corinne at any time t is given by D = 0.125t while the distance from the starting point of Aretha at any time t is given by D = 3.5 + 0.1t

Let t be the number of minutes after the start of the race when Corinne catchs Aretha, then

0.125t = 3.5 + 0.1t
0.025t = 3.5
t = 3.5 / 0.025 = 140

Therefore, the number of <span>minutes after the start of the race that Corinne will catch Aretha</span> is 140 minutes.
6 0
2 years ago
Read 2 more answers
If LN=54 and LM=31, find MN
kirza4 [7]
In this item, it is unfortunate that a figure, drawing, or illustration is not given. To be able to answer this, it is assumed that these segments are collinear. Points L, M, and N are collinear, and that L lies between MN. 

The length of the whole segment MN is the sum of the length of the subsegments, LN and LM. This can be mathematically expressed,
             LN + LM = MN

We are given with the lengths of the smalller segments and substituting the known values,
             MN = 54 + 31
            MN = 85

<em>ANSWER: MN = 85</em>
7 0
1 year ago
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A clothing store is analyzing merchandise prices to help make decisions on what to charge for clothing on clearance. The store o
Aleks [24]

The variable is Quantitative, has Interval level of measurement.

Variables which can be quantified & expressed numerically are Quantitative variables. Eg : as given , price

Variables which cant be qualified & expressed numerically are Qualitative variables. Eg : level of honesty, loyalty etc

Nominal & Ordinal are qualitative variables : signifying yes or no to a category (like men or women) , or ranks (x better than y) respectively. So price level is not such categorical & ordinal ratio.

Quantitative ratio variables are with reference to time , or are in forms of rate (like speed , growth per year). So, price level is not such ratio variable also.

Price is a quantitative variable, in which the ranking, its difference can be calculated. This is characteristic of a <u>Quantitative Interval Variable</u>.

4 0
1 year ago
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