Wats the diameter and radius of a circle in 9 yards

As a motorcycle accelerates at 5.1 m/s2, its speed changes from 16 km/h to 118 km/h. How long does this take?

ser-zykov [4K]

Acceleration (a) = 5.1 m/s²
Initial speed (u) = 16 km/h ⇒ $\frac{16*1000}{3600}$ m/s ≈ 4.5m/s
Final speed (v) =118 km/h ⇒ $\frac{118*1000}{3600}$ m/s ≈ 32.8m/s

Distance(S) travel in that particular instant is carried out by 'Third equation of motion' i.e., v² = u² + 2aS

So, When all quantities are in S.I. unit then,
putting the values in the equation of motion,

As we have to carry out the distance covered,
2·a·S = v² - u²
S = $\frac{ v^{2} - u^{2} }{2a}$
Putting values in derived equation,
⇒ S = $\frac{ (32.8)^{2} - (4.5)^{2} }{2*(5.1)}$
⇒ S = $\frac{ 1075.84 - 20.25}{10.2}$
⇒ S = $\frac{1055.59}{10.2}$
⇒ S ≈ 103.489 m

The total distance covered in that given condition is approx. 103.289 m.

8 0

3 years ago

Read 2 more answers

Which mathematical concept did you use to find the number of gumballs that fit INSIDE the package?

Vlada [557]

The answer is Volume

5 0

2 years ago

The Rocky Mountain district sales manager of Rath Publishing Inc., a college textbook publishing company, claims that the sales

mihalych1998 [28]

Answer:

We conclude that the mean number of calls per salesperson per week is more than 37.

Step-by-step explanation:

We are given that the Rocky Mountain district sales manager of Rath Publishing Inc., a college textbook publishing company, claims that the sales representatives make an average of 37 sales calls per week on professors.

To investigate, a random sample of 41 sales representatives reveals that the mean number of calls made last week was 40. The standard deviation of the sample is 5.6 calls.

Let $\mu$ = true mean number of calls per salesperson per week.

SO, Null Hypothesis, $H_0$ : $\mu \leq$ 37 {means that the mean number of calls per salesperson per week is less than or equal to 37}

Alternate Hypothesis, $H_A$ : $\mu$ > 37 {means that the mean number of calls per salesperson per week is more than 37}

The test statistics that will be used here is One-sample t test statistics as we don't know about the population standard deviation;

T.S. = $\frac{\bar X -\mu}{\frac{s}{\sqrt{n} } }$ ~ $t_n_-_1$

where, $\bar X$ = sample mean number of calls made last week = 40

s = sample standard deviation = 5.6 calls

n = sample of sale representatives = 41

So, test statistics = $\frac{40-37}{\frac{5.6}{\sqrt{41} } }$ ~ $t_4_0$

= 3.43

Hence, the value of test statistics is 3.43.

Now at 0.025 significance level, the t table gives critical value of 2.021 at 40 degree of freedom for right-tailed test. Since our test statistics is more than the critical value of t as 3.43 > 2.021, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region.

Therefore, we conclude that the mean number of calls per salesperson per week is more than 37.

4 0

3 years ago

Write the expression 12 x 4^2 in words

lawyer [7]

Answer and Step-by-step explanation:

Twelve times four squared.

This is how you would write the expression in word format.

#teamtrees #PAW (Plant And Water)

7 0

3 years ago

Conditional Distribution, Marginal Distribution, Joint Distribution. What’s the difference?

lutik1710 [3]

Explanation:

Marginal distribution: This distribution gives the probability for each possible value of the Random variable ignoring other random variables. Basically, the values of other variables is not considered in the marginal distribution, they can be any value possible. For example, if you have two variables X and Y, the probability of X being equal to a value, lets say, 4, contemplates every possible scenario where X is equal to 4, independently of the value Y has taken. If you want the probability of a dice being a multiple of 3, you are interested that the dice is either 3 or 6, but you dont care if the dice is even or odd.

Conditional distribution: This distribution contrasts from the previous one in the sense that we are restricting the universe of events to specific condition for other variable, making a modification of our marginal results. If we know that throwing a dice will give us a result higher than 2, then to in order to calculate the probability of the dice being a multiple of 3 using that condition, we have two favourable cases (3 and 6) from 4 total possible results (3,4,5 and 6) discarding the impossible values (1 and 2) from this universe since they dont match the condition given (note that the restrictions given can also reduce the total of favourable cases).

The joint distribution calculates the probabilities for two different events (related to two different random variables) occuring simultaneously. If we want to calculate the joint probability of a dice being multiple of 3 and greater than 2 at the same time, our possible cases in this case are 3 and 6 from 6 possible results. We are not discarding 1 or 2 as possible results because we are not assuming, that the dice is greater than 2, that is another condition that we should met in the combination of events.

3 0

3 years ago