Answer:
x = -4, 14
Step-by-step explanation:
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Answer:
260,000
Step-by-step explanation:
The value decreases by 40,000 per year (500000-42000/2 years) the value will decrease by 240000 in six (4 years plus 2 years already passed) years. 6 x 40,000 =240000
So, the value should be 260,000 (500000-240000)
Or
year 1 500000-40000=460000
year 2 460000-40000=420000
year 3 420000-40000=380000
year 4 380000-40000=340000
year 5 340000-40000=300000
year 6 300000-40000=260000
Answer:
10000*0.6065=6065
A. about 6,065
Step-by-step explanation:
Definitions and concepts
The Poisson process is useful when we want to analyze the probability of ocurrence of an event in a time specified. The probability distribution for a random variable X following the Poisson distribution is given by:
And the parameter 
represent the average ocurrence rate per unit of time.
For this distribution the expected value is the same parameter
, 
, 
Solution to the problem
We want "how many would have no blemishes" so first we need to find the probability that X=0, since X represent on this case the number of blemishes on each door. And if we use the mass function we got this:
And now since we have a total of 10000 doors painted we can find how many we would expect with no blemishes:
10000*0.6065=6065
A. about 6,065
Answer as a fraction = 1/5040
Answer in decimal form (approximate) = 0.000198
Answer in percentage form (approximate) = 0.0198%
=========================================================
Explanation:
There is only one ordering of the letters to get DESIGN out of 5040 different permutations. The 5040 comes from the fact that 7*6*5*4*3*2*1 = 5040. In shorthand notation, use factorials to say 7! = 5040. Notice how we started with 7 and counted down until reaching 1, multiplying all along the way. You could use the nPr permutation formula to get the same result of 5040 (use n = 7 and r = 7).
So because we have 1 way to order the letters (getting DESIGN) out of 5040 ways total, this means the probability is the fraction 1/5040. Use your calculator to find that 1/5040 = 0.000198 approximately. Move the decimal over 2 spots to the right to convert 0.000198 to 0.0198%
Answer:
The data provide strong evidence that young men weigh more on average than old men in the U.S
Step-by-step explanation:
Given :
The null hypothesis ; H0 : μ1 = μ2
The alternative hypothesis ; H1 : μ1 > μ2
T score = 5.3 ; Pvalue = < 0.0001
The decision region :
If Pvalue < α ; We reject the Null
If Pvalue > α ; We fail to reject the Null
When the α - level isn't stated, we usually assume a α - level of 5%
However, even at lower alpha level of 1% = 0.01 ;
The Pvalue < α
Hence, we can conclude that there is significant evidence that there is difference in the mean weight of young men and old men in the U.S
