Answer:
A quick comparison of the sample variances suggests that the population variances <u><em>are same or almost equal.</em></u>
Step-by-step explanation:
The populations from which two samples are drawn are normally distributed.
The variable used to predict another variable is called an independent variable.
F- distribution is used for the test of two sample hypotheses of variances.
If two populations have equal variances then the test Statistic is nearly equal to 1.
<em>t= s²₁/s²₂i</em>
<em />
As the variances are almost or nearly equal the test statistic would be almost equal to 1.
2/3 meters would be a reasonable estimate.
Answer:
Multiply by ∛2 and translate the graph to left by 4 units.
Step-by-step explanation:
The initial function given is:
y = -∛(x - 4)
The transformed function is:
y = -∛(2x - 4)
Consider the initial function.
y = -∛(x - 4)
(Represented by Black line in the graph)
Multiply the function by ∛2. The function becomes:
y = -∛(x - 4) × ∛2
y = -∛(2)(x-4)
y = -∛(2x-8)
(Represented by Red line in the graph represents this function)
Translate the graph 4 units to the left by adding 4 to the x component:
y = -∛(2x-8+4)
y= -∛(2x - 4)
(Represented by Blue line in the graph)
Answer:
0.24315
Step-by-step explanation:
Using the z score formula to solve this question
z = (x - μ) / σ,
Such that:
x = raw score
μ = population mean
σ = population standard deviation.
From the question:
x = 3000
μ = 3550
σ = 870
z = (3000 - 3550) / 870
z = -550/870
z = -0.6962
Using the z score table as well as probability calculator(as requested in the question to find the z score)
The probability of having less than 3000 is obtained as:
P(x<3000) = 0.24315
