2022-02-23
Answered

What is the probability that exactly 3 heads will appear if a coin is tossed 4 times

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alenahelenash

Answered 2022-03-10
Author has **368** answers

N=3: To get 3 heads, means that one gets only one tail. This tail can be either the 1st coin, the 2nd coin, the 3rd, or the 4th coin. Thus there are only 4 outcomes which have three heads. The probability is 4/16 = 1/4.

asked 2021-02-25

Explain why t distributions tend to be flatter and more spread out than the normal distribution.

asked 2021-05-03

Describe in words the surface whose equation is given. (assume that r is not negative.) $\theta =\frac{\pi}{4}$

a) The plane$y=-z$ where y is not negative

b) The plane$y=z$ where y and z are not negative

c) The plane$y=x$ where x and y are not negative

d) The plane$y=-x$ where y is not negative

e) The plane$x=z$ where x and y are not negative

a) The plane

b) The plane

c) The plane

d) The plane

e) The plane

asked 2021-02-27

The manager of the store in the preceding exercise calculated the residual for each point in the scatterplot and made a dotplot of the residuals.

The distribution of residuals is roughly Normal with a mean of $0 and standard deviation of $22.92.

The middle 95% of residuals should be between which two values? Use this information to give an interval of plausible values for the weekly sales revenue if 5 linear feet are allocated to the stores

The distribution of residuals is roughly Normal with a mean of $0 and standard deviation of $22.92.

The middle 95% of residuals should be between which two values? Use this information to give an interval of plausible values for the weekly sales revenue if 5 linear feet are allocated to the stores

asked 2022-08-09

Approximating the following system using ordinary least squares regression

$y={p}_{0}+{p}_{1}{x}_{1}+{p}_{2}{x}_{2}+...{p}_{M}{x}_{M}=\xi P$

I know that a property of the least squares estimator is that the sum of the residuals, ${r}_{i}={\hat{y}}_{i}-{y}_{i}$, is equal to zero. However, what I am finding is that the sum of the residuals multiplied by one of the regressors, ${\xi}_{m}\in (\mathbf{1},{x}_{1},{x}_{2},...,{x}_{M})$, is also equal to zero. I have found this to be true in all cases in simulation, but I am not sure how to prove it.

$\sum _{i=0}^{N}{r}_{i}{\xi}_{m}=0$

$y={p}_{0}+{p}_{1}{x}_{1}+{p}_{2}{x}_{2}+...{p}_{M}{x}_{M}=\xi P$

I know that a property of the least squares estimator is that the sum of the residuals, ${r}_{i}={\hat{y}}_{i}-{y}_{i}$, is equal to zero. However, what I am finding is that the sum of the residuals multiplied by one of the regressors, ${\xi}_{m}\in (\mathbf{1},{x}_{1},{x}_{2},...,{x}_{M})$, is also equal to zero. I have found this to be true in all cases in simulation, but I am not sure how to prove it.

$\sum _{i=0}^{N}{r}_{i}{\xi}_{m}=0$

asked 2021-09-18

A group of children and adults were polled about whether they watch a particular TV show. The survey results, showing the joint relative frequencies and marginal relative frequencies, are shown in the two-way table. What is the value of x?
YesNoTotal Children0.30.40.7 Adults0.25x0.3 Total0.550.451

asked 2021-09-20

Use the two-way table of data from another student survey to answer the following question.

Find the conditional relative frequency that a student likes to lift weights, given that the student likes aerobics.

asked 2021-02-10

Suppose x1 and x2 are predictor variables for a response variable y.

a. The distribution of all possible values of the response variable corresponding to particular values of the two predictor variables is called a distribution of the response variable.

b. State the four assumptions for multiple linear regression inferences

a. The distribution of all possible values of the response variable corresponding to particular values of the two predictor variables is called a distribution of the response variable.

b. State the four assumptions for multiple linear regression inferences