Real quick<br><br> what is the radius of 16 cm simplest form

The life times of light bulbs produced by a particular manufacturer have a mean of 1,200 hours and a standard deviation of 400 h

Nezavi [6.7K]

Answer:

a. 1200hours

b. σ² = 400² =160000hour

c. standard error = 133.33

d. for 9 lightbulb it is likely that 9*0.146 = 1.31 bulbs will have lives of fewer than 1,050 hours?

Step-by-step explanation:

mean of 1,200 hours

σ, a standard deviation of 400 hours.

Sample size, N = nine bulbs,

a) mean of the sample mean lifetime: is given as 1,200 hours

b) variance of the sample mean is the square of the σ, a standard deviation of 400 hours.

σ² = 400² =160000hours

c) What is the standard error of the sample mean?

The standard deviation of a sampling distribution of mean values is called the standard error of the means,

standard error of the means, σx = σ √N

The formula for the standard error of the means is true for all values infinite number of sample, N.

σx = σ √N

=400 √9 = 400/3 =133.3333

d) the probability that, on average, those nine lightbulbs have lives of fewer than 1,050 hours

The area under part of a normal probability curve is directly proportional to probability and the value is calculated as

z = ( x₁−x) /σ

where z = propability of normal curve

x₁ = variate mean = 1050hours

x = mean of 1200hours

σ = standard deviation = 400

applying the formula,

z= (1050-1200)/400

z = 150/400 =0.375

Using a table of partial areas beneath the standardized normal curve (see Table of normal curve, a z-value of 0.375 corresponds to an area of 0.1460 between the mean value.

Thus the probability of a lightbulbs having lives of fewer than 1,050 hours is 0.1460.

for 9 lightbulb it is likely that 9*0.146 i.e. 1.31 bulbs will have lives of fewer than 1,050 hours?

8 0

3 years ago

YOU DONT HAVE TO DO ALL IF YOU DONT WANT TO JUST DO WHAT YOU CAN

Vikki [24]

Answer:

(Warning) Not sure this is completley correct but this is just what I did.

Part A

Does the data for Amit’s puppy show a function? Why or why not?

It does show a function because it passes the vertical line test (no two points have the same x value).

Part B

Is the relationship for Amit’s puppy’s weight in terms of time linear or nonlinear? Explain your response.

Nonlinear because the line isn’t straight

Part C

Is the relationship between Amit’s puppy’s weight in terms of time increasing or decreasing? Explain your response.

Increasing because it is gaining weight

Part D

Does the data for Camille’s puppy show a function? Why or why not?

Yes, it does, because each input value has a unique output value

Part E

Is the relationship for Camille’s puppy’s weight in terms of time linear or nonlinear? Explain your response.

It is a linear function because the line has no curve, and the line is constant.

Part F

Is the relationship between Camille’s puppy’s weight in terms of time increasing or decreasing? Explain your response.

Increasing because as the puppy gets older it gains weight.

Part G

Does the data for Olivia’s puppy show a function? Why or why not?

Yes, it does, because each input value has a unique output value. The graph attached ( which shows the data for Camille’s puppy), that each x-value (Weeks) has a unique y-value (Weight in pounds).

Therefore, based on this and keeping in mind the explanation before, you can conclude that the data for Camille’s puppy shows a function.

Part H

Is the relationship for Olivia’s puppy’s weight in terms of time linear or nonlinear? Explain your response

Yes, it linear because it’s a straight line.

Part I

Is the relationship for Olivia’s puppy’s weight in terms of time increasing or decreasing? Explain your response. Increasing. For every week that goes by, Olivia's puppy is gaining one pound. 6-5= 1 14-13= 1. Gaining a pound every week makes the puppy’s weight increase.

Part J

Which two relationships have a y-intercept and a constant rate of change?

They all have y-intercepts and only Olivia and camilles have a constant rate of change.

Part A

To compare the linear functions, you first need to find their equations. For each of the linear functions, write an equation to represent the puppy’s weight in terms of the number of weeks since the person got the puppy.

Linear equation, y=mx+b

Exponential equation, y=a(b)×

Part B

Now you can compare the functions. In each equation, what do the slope and y-intercept represent in terms of the situation?

The y-intercept in the situation is 2/6.

Part C

Whose puppy weighed the most when the person got it? How much did it weigh?

Olivia’s puppy, it weighed 5 pounds

Part D

Whose puppy gained weight the slowest? How much did it gain per week?

Olivia’s puppy gained weight the slowest because it started off with more weight but only gained around 1 pound every week.

Part E

You can also graph the functions to compare them. Using the Edmentum Graphing Tool, graph the two linear functions. Paste a screenshot of the two functions in the space provided. How could you find which puppy had a greater initial weight from the graph? How could you find which puppy gained weight the slowest?

The edmentum graphing tool is opening up I tried it more than once but, the linear graphs would be Camille puppy and olivia's. And I could tell which one had a greater weight by how much they had at week 1 and how much they gained the weeks later. I could find which puppy gained weight the slowest by looking at the weight gained and graphed.

Step-by-step explanation:

6 0

3 years ago

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