Hello,

at a football game 95% of people attending were supporting the home team while 5% were supporting the visiting team. if the tota

Paraphin [41]

Answer:

3800

Step-by-step explanation:

The first step you want to do is make a proportion

x/4000=95/100

Next you are going to cross multiply which his 4000 times 95 equals 380000 and then multiply 100 times x which is 100x.

Then you are going to divide both sides by 100 and you will cross out the x from the 100 and get only x and then divide 380000 divided by 100 and 3800

Which leaves you with x=3800

3800 people were attending to support the home team

Hope this helps :)

5 0

3 years ago

A company interested in lumbering rights for a certain tract of slash pine trees is told that the mean diameter of these trees i

brilliants [131]

Answer:

97.6% of the trees will have diameters between 7.6 and 18.6 inches.

Step-by-step explanation:

We are given the following information in the question:

Mean, μ = 12 inches

Standard Deviation, σ = 2.2 inches

We are given that the distribution of diameter of tree is a mound shaped distribution that is a normal distribution.

Formula:

$z_{score} = \displaystyle\frac{x-\mu}{\sigma}$

P(diameters between 7.6 and 18.6 inches)

$P(7.6 \leq x \leq 18.6) = P(\displaystyle\frac{7.6 - 12}{2.2} \leq z \leq \displaystyle\frac{18.6-12}{2.2}) = P(-2 \leq z \leq 3)\\\\= P(z \leq 3) - P(z < -2)\\= 0.999 - 0.023 = 0.976= 97.6\%$

$P(7.6 \leq x \leq 18.6) = 97.6\%$

97.6% of the trees will have diameters between 7.6 and 18.6 inches.

8 0

3 years ago

Exploring the graph of y equals cosine Theta

irga5000 [103]

Answer: see below

<u>Step-by-step explanation:</u>

The coordinates on the Unit Circle are (cos, sin). Since we are focused on cosine, we only need to focus on the left side of the coordinate. The cosine value (left side) will be the y-value of the function y = cos x

Use the quadrangles (angles on the axes) to represent the x-values of the function y = cos x.

Quadrangles are: 0°, 90°, 180°, 270°, 360° <em>(360° = 0°)</em>

Together, the coordinates will be as follow:

$\boxed{\begin{array}{c||c|c||c}\underline{(cos,sin)}&\underline{x=angle}&\underline{y=cosx}&\underline{\quad (x,y)\quad}\\(1,0)&0^o&1&(0^o,1)\\(0,1)&90^o&0&(90^o,0)\\(-1,0)&180^o&-1&(180^o,-1)\\(0,-1)&270^o&0&(270^o,0)\\(1,0)&360^o&1&(360^o,1)\end{array}}$

8 0

3 years ago

The large pizza is 16 inch what the circumference plz help

tatuchka [14]

Answer:

50.265 inches

Step-by-step explanation:

4 0

3 years ago

The effect of a monetary incentive on performance on a cognitive task was investigated. The researcher predicted that greater mo

riadik2000 [5.3K]

Answer:

1) $H_0:\mu_5=\mu_{25}=\mu_{50}$

2) $H_a:\mu_{50}>\mu_{25}>\mu_{5}$

3) A Type I error happens when we reject a null hypothesis that is true. In this case, that would mean that the conclusion is that there is evidence to support the claim that the greater the incentive, the more puzzles are solved, but that in reality there is no significant difference.

4) A Type II error happens when a false null hypothesis is failed to be rejected. In this case, that would mean that there is no enough evidence to support the claim that the greater the incentive, the more puzzles are solved, but in fact this is true.

5) The probability of a Type I error is equal to the significance level, as this is the chance of having a sample result that will make the null hypothesis be rejected.

Step-by-step explanation:

As the claim is that the greater the incentive, the more puzzles were solved, the null hypothesis will state that this claim is not true. That is that there is no significant relation between the incentive and the amount of puzzles that are solved. In other words, the mean amount of puzzles solved for the different incentives is equal (or not significantly different):

$H_0:\mu_5=\mu_{25}=\mu_{50}$

The research (or alternative hypothesis) is that the greater the incentive, the more puzzles were solved. That means that the mean puzzles solved for an incentive of 50 cents is significantly higher than the mean mean puzzles solved for an incentive of 25 cents and this is significantly higher than the mean puzzles solved for an incentive of 5 cents.

$H_a:\mu_{50}>\mu_{25}>\mu_{5}$

A Type I error happens when we reject a null hypothesis that is true. In this case, that would mean that the conclusion is that there is evidence to support the claim that the greater the incentive, the more puzzles are solved, but that in reality there is no significant difference.

A Type II error happens when a false null hypothesis is failed to be rejected. In this case, that would mean that there is no enough evidence to support the claim that the greater the incentive, the more puzzles are solved, but in fact this is true.

The probability of a Type I error is equal to the significance level, as this is the chance of having a sample result that will make the null hypothesis be rejected.

4 0

3 years ago