PRE CALC QUESTION

Mitchell is one of the goalies for an ice hockey team. He wants to be goalie in the game today, but that depends on who coaches

seropon [69]

Answer:

49% probability that Mitchell will be a goalie today

Step-by-step explanation:

Coach White coaches with 70% probability. So 70% of the time, there is a 55% probability that Mitchell is the goalie.

The other 100-70 = 30% of the time, 35% probability that Mitchell will be the goalie.

What is the probability that Mitchell will be a goalie today?

$P = 0.7*0.55 + 0.3*0.35 = 0.49$

49% probability that Mitchell will be a goalie today

8 0

3 years ago

Which word is an antonym of strenuous? here are the options Easy Weak

Pepsi [2]

Answer:

the answer is easy

Step-by-step explanation:

3 0

3 years ago

Read 2 more answers

Consider the two different numbers 327b (327 is base b) and 327b 1 (327 in base b 1), where b is a positive integer 8 or greater

Nata [24]

Answer:

Value of b = 14

Step-by-step explanation:

The detailed calculations with steps is shown in the attachment.

5 0

4 years ago

In a lottery game, a player picks 5 numbers from 1 to 46. If 4 of the 5 numbers match those drawn, the player wins second prize.

Umnica [9.8K]

Answer:

Step-by-step explanation:

given that in a lottery game, a player picks 5 numbers from 1 to 46

If 4 of the 5 numbers match those drawn, the player wins second prize.

Assuming the numbers are chosen without repitition we find that the player can choose 5 numbers in 46C5 ways.

To win the prize he must choose 4 numbers form the 5 numbers in the prize and remaining 1 number any other number.

i.e. no of ways to get II price = choosing 4 numbers out of 5, and one number from 41

= $5C4*41C1 = 205$

Probability of winning this prize

= $\frac{205}{46C5} \\= \frac{205*5(4)(3)(2)1}{46*45*44*43*42} \\=\frac{41*5*2*3}{46*9*22*43*21} \\=\frac{205}{1370754}$

6 0

3 years ago

Both the variance and standard deviation are intended to provide a measure of the variability of a set of data values about

dezoksy [38]

Answer:

Step-by-step explanation:

Hello!

The variance and standard deviation of a distribution are measurements of dispersion. They show the degree of variation of the values of a dataset regarding the mean.

Variance:

The variance is defined as the mean of the squares of the difference between the values of the variable and the mean, symbolically:

V(X)= S²= E(X-X[bar])²=   $\left \ {{n} \atop {i = 1}} \right.$ ∑( $X_i$ -X[bar])² 

n

Properties:

1. The variance is non-negative:

V(X) ≥ 0

Since it is calculated as the summation of squared values it is not possible for it to be negative.

2. The variance of a constant (k) is zero:

V(k)= E(k-k)²= 0

3. The variance is unaffected by changes in the parameters of position, so if for example, a constant is added to the variable X+k, since it is added to all values of the variable, the variance remains unchanged:

V(X+k)= V(X)

Same happens if a constant is subtracted from the variable:

V(X-k)= V(X)

4. If you multiply the variable X by a constant k, the resulting variance will be the variance of the variable by the square of the constant:

V(X*k)= k² * V(X)

5. If you add or subtract two independent variables, the resulting variance for both cases will be the summation of their variances:

V(X±Y)= V(X)+V(Y)

When you add or subtract two dependent variables, the variance of the resulting variable will be the summation of both variances minus their covariance:

V(X±Y)= V(X)+V(Y)-Cov(XY)

Note: covariance is the measure of joint variability of two random variables.

Standard deviation:

The standard deviation is defined as the square root of the variance. The properties of the variance apply to it too.

This measurement is often chosen over the variance since is easier to express the dispersion of a variable over non-square units or values.

S= √S²

I hope this helps!

6 0

3 years ago