Answer:
32
Step-by-step explanation:
XY means x times y
and x = 8 or x is 8
and y = 4 or y is 4
so 4 times 8 is 32
so
XY = 32
<span>(a) This is a binomial
experiment since there are only two possible results for each data point: a flight is either on time (p = 80% = 0.8) or late (q = 1 - p = 1 - 0.8 = 0.2).
(b) Using the formula:</span><span>
P(r out of n) = (nCr)(p^r)(q^(n-r)), where n = 10 flights, r = the number of flights that arrive on time:
P(7/10) = (10C7)(0.8)^7 (0.2)^(10 - 7) = 0.2013
Therefore, there is a 0.2013 chance that exactly 7 of 10 flights will arrive on time.
(c) Fewer
than 7 flights are on time means that we must add up the probabilities for P(0/10) up to P(6/10).
Following the same formula (this can be done using a summation on a calculator, or using Excel, to make things faster):
P(0/10) + P(1/10) + ... + P(6/10) = 0.1209
This means that there is a 0.1209 chance that less than 7 flights will be on time.
(d) The probability that at least 7 flights are on time is the exact opposite of part (c), where less than 7 flights are on time. So instead of calculating each formula from scratch, we can simply subtract the answer in part (c) from 1.
1 - 0.1209 = 0.8791.
So there is a 0.8791 chance that at least 7 flights arrive on time.
(e) For this, we must add up P(5/10) + P(6/10) + P(7/10), which gives us
0.0264 + 0.0881 + 0.2013 = 0.3158, so the probability that between 5 to 7 flights arrive on time is 0.3158.
</span>
Answer:
I believe it would be 16
Step-by-step explanation:
8 is half of 16 and if she had 8 dollars after spending half her allowance, she would've had 16 as her allowance
Final answer: Her allowance would be 16 dollars
Answer:
<h2>y-intercept = 3</h2><h2>x-intercept - not exist</h2><h2>the graph is increasing</h2>
Step-by-step explanation:
The exponential function:
has y-intercept for x = 0
hasn't x-intercept
if a > 1, then is increasing
if 0 < a < 1, then is decreasing
We have
a = 2 >1 - increasing
for x = 0:
Answer:
B. load-distance model
Step-by-step explanation:
A. trial and error
Trial and error is "a fundamental method of problem solving. It is characterised by repeated, varied attempts which are continued until success". But this method is not the best in order to compare effectiveness of layouts
B. load-distance model
The load-distance method is a "mathematical model used to evaluate locations based on proximity factors. The objective is to select a location that minimizes the total weighted loads moving into and out of the facility. The distance between two points is expressed by assigning the points to grid coordinates on a map". And that's the correct option since we are trying to measure the effectiveness of layouts quantitatively.
C. exponential smoothing
This is "a rule of thumb technique for smoothing time series data using the exponential window function". Wheighting observations using the exponential function. But this is a techinique used to smooth s time series not to compare effectiveness of layouts.
D.process control charts
The Control Chart is a "graph used to study how a process changes over time with data plotted in time order". But we don't want to see how the process changes the objective is quantitatively compare the effectiveness of layouts, and this one is not the best option for this.
E. mean absolute deviation (MAD)
The median absolute deviation(MAD) is "a robust measure of how spread out a set of data is. The variance and standard deviation are also measures of spread, but they are more affected by extremely high or extremely low values and non normality". But again is just a measure of spread and not allow to compare effectiveness of layouts.
