Answer:
B.
Step-by-step explanation:
Since the variable <em>b</em> is manipulated in f(x) = a(bx - h)² + k, we are dealing with horizontal compression and stretching. Since b < 1, that means the graph is being horizontally compressed.
Answer:
k>8
Step-by-step explanation:
k more than 8 indicates that the value of k is larger than 8. So the inequality sign opens towards k and closes towards 8.
Hope this helps!
Answer:
(364.595 ; 391.405)
Step-by-step explanation:
Given the sample data:
406, 385, 389, 383, 352, 379, 388, 343, 368, 387
Using calculator :
Sample mean, xbar = 378
Standard deviation, s = 18.74
Confidence interval :
Xbar ± Margin of error
Margin of Error = Tcritical * s/√n
TCritical at df = 24 ; 0.05 = 2.262
Margin of Error = 2.262 * 18.74/√10 = 13.405
Lower boundary = (378 - 13.405) = 364.595
Upper boundary = (378 + 13.405) = 391.405
(364.595 ; 391.405)
The missing data value according to the given z-score is <u>39</u>.
We can determine how distant a data point is from the mean using its z-score. It is a crucial subject in statistics. Z-scores are a way to compare data to a population that is considered "normal." When attempting to compare someone's weight to that of the "average" person, for instance, it might be intimidating to look at a large table of data even though we know they weigh 70 kg. A z-score offers us an indication of how that person's weight compares to the mean weight of the general population. We shall discover what the z score is in this post.
The z score is a measurement of how many standard deviations a raw score is below or above the population mean. If the value is higher than the mean, it will be positive; if it is lower, it will be negative. The standard score is another name for it. It shows how far away from the mean an object is, in terms of standard deviations. The mean and population standard deviation must be known to apply a z-score. The likelihood of a score happening inside a typical normal distribution may be calculated with the use of a z score. We may also compare two scores from other samples thanks to it. A z score table is a table that contains the values of, which represent the cumulative distribution function of the normal distribution.
The equation is given by z = (x – μ)/ σ.
μ = mean
σ = standard deviation
x = test value.
In the question, z = -2.1, μ = 43, and σ = 2.
Substituting the values, we get:
-2.1 = (x - 43)/2,
or, x - 43 = -2.1*2,
or, x = -4.2 + 43,
or, x = 38.8 ≈ 39.
Thus, the missing data value according to the given z-score is <u>39</u>.
Learn more about z-scores at
brainly.com/question/10679480
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