Measure in degrees of x. someone please help options are listed!!!

In an ANOVA, if the null hypothesis is true we expect the F value to be:

masya89 [10]

Answer
C
Explanation

3 0

2 years ago

Plz help me with this

zvonat [6]

Answer: 5 cos x

Step-by-step explanation:

y = sin x is y = cos x shifted to the right π/2 units.

y = 5 sin (x + π/2) is a shift to the left π/2 units (which results in cos x) and . an amplitude of 5.

--> y = 5 cos x

8 0

3 years ago

The probability that Brock scores a penalty kick is LaTeX: \frac{3}{10}3 10 . If he shoots 50 penalty kicks, how many "goals" ca

Feliz [49]

Answer:

15 goals out of 50 penalty kicks was scored by brock

Step-by-step explanation:

If Brock shoots 50 penalty kicks and the probability that he scores a penalty kick is 3/10, the number of goal brock is expected to make can be expressed as:

Number of goals scored = probability value * total penalty kicks taken

Number of goals scored = $\frac{3}{10}*50$

Number of goals scored = $15 goals$

5 0

3 years ago

I think of a number and multiply it by 4. I then add 8 and I'm left with an answer of 30. What number did I think of? Form and s

postnew [5]

Answer: number= 5.5; equation: 4x+8=30

Step-by-step explanation:

Take x for the unknown number. Then just follow the words and turn them into mathematical symbols. Easy.

5 0

3 years ago

Police use a radar unit is used to measure speeds of cars on a freeway. The speeds are normally distributed with a mean of 90 km

vagabundo [1.1K]

Answer:

A. P(x≥100)=0.1587

B. P(x≤0)≈0

Step-by-step explanation:

A. Cause we know the distribution of the data, the method used to solve it is called "Normalization" and we need to have the Mean and the Standard deviation of the data. The method consist in the following equation

P(x≤a)=P( z=((x-μ)/σ) ≤ b=((a-μ)/σ) )

Considering μ as the Mean and σ as the Standard deviation. At first, we had a probability in the normal distribution with Mean=90 and STD=10 but that kind of exercises is not meant to find that probability directly but by using this process.

After we normalize the probability, now we have a probability in a specific normal distribution that has Mean=0 and STD=1 and the difference with what we had before is that now we are able to use tools to find probabilities in a normal standard distribution. My favorite of them is a chart that show the approximate values of a lot of probabilities (i attached it to this answer). I´m going to explain point A as an example:

We look for the probability that P(x≥100), but we don´t have an easy method to use there, so we normalize:

P(x≥100)=P( (x-μ)/σ ≥ (100-μ)/σ )

P(x≥100)=P( z ≥ (100-90)/10 )

P(x≥100)=P( z ≥ 1 )

And now we are able to use the chart, let me explain: First, the chart only works with P(z ≤ b), so we have to change it with properties of probabilities before using the table.

P(z≥1)=1-P(z≤1)

And finally we use the chart:

the value of P(z≤1) is in the table, we look for the row with +1 and the column with the decimal part (in this case 0) and with coordinates (1,0) there´s the value:

P(z≤1)=0.8413

But we need P(z≥1) so we use the previous equality

P(z≥1)=1-P(z≤1)

P(z≥1)=1-0.8413

P(z≥1)=0.1587

Because P(x≥100)=P(z≥1), our final answer is 0.1587

B. We use the same process to try to understand what the probability of P(x≤0) represents.

P(x≤0)=P(z≤ (0-90)/10)

P(x≤0)=P( z ≤ -9 )

But when we try to look for its value in the chart It isn´t even there, what could it mean?

A normal distribution function is always increasing, that means that "a≤b if and only if P(x≤a) ≤ P(x≤b)". so we conclude:

P(z≤-9) ≤ P(z≤-3) (The lowest probability in the chart)

P(z≤-9) ≤ 0.0013

P(z≤-9) is way lower than 0.0013 (they aren´t even close) but we know that probability is always positive, and because of that:

P(x≤0)=P(z≤-9)≈0

5 0

3 years ago