4*(2x+1)=(2x+1)+(2x+1)+(2x+1)+(2x+1)=
2x+2x+2x+2x+1+1+1+1=
=8x+4
I hope this is ok !
We are to find the probability that the weight of total luggage for a sample of 100 passengers is less than 2100.
The mean weight of the luggage of passengers will be 2100/100 = 21.
So we have to find the probability of the mean weight to be less than 21.
Average weight = u = 19.4
Standard deviation = 5.3
Since we are dealing with a sample of 100. We will use the standard error.
Standard error =

Now we have to convert the weight to z-score

From z table we can find the probability of z being less than 3.018 is 99.87%.
Therefore, the probability that for (a random sample of) 100 passengers, the total luggage weight is less than 2,100 lbs is 99.87%
The slope would be 58.
Slope = (change in y) / (change in x)
That relationship is established by the fixed cost of each ticket ($58). The handling fee is a constant that would shift the curve upward by $5, but would have no effect on the slope of the line since it is completely independent from the number of tickets being purchased (x).
Answer:
10
Step-by-step explanation:
The number of tiles in the design is 1 + 2 + 3 + ...
We can model this as an arithmetic series, where the first term is 1 and the common difference is 1. The sum of the first n terms of an arithmetic series is:
S = n/2 (2a₁ + d (n − 1))
Given that a₁ = 1 and d = 1:
S = n/2 (2(1) + n − 1)
S = n/2 (n + 1)
Since S ≤ 60:
n/2 (n + 1) ≤ 60
n (n + 1) ≤ 120
n must be an integer, so from trial and error:
n ≤ 10
Mr. Tong should use 10 tiles in the final row to use the most tiles possible.
Answer:
d) The difference exists due to chance since the test statistic is small
Step-by-step explanation:
From the given information:
Population mean = 178 cm
the sample mean = 177.5 cm
the standard deviation = 2
the sample size = 25
The null hypothesis and the alternative hypothesis can be computed as:
Null hypothesis:

Alternative hypothesis:

The t-test statistics is determined by using the formula:




Degree of freedom df = n- 1
Degree of freedom df = 25 - 1
Degree of freedom df = 24
At the level of significance ∝ = 0.05, the critical value = 2.064
Decision rule: To reject the null hypothesis if the test statistics is greater than the critical value at 0.05 level of significance
Conclusion: We fail to reject the null hypothesis since the test statistics is lesser than the critical value and we conclude that the difference exists due to chance since the test statistic is small