No, we can only suppose that the observed distribution deviates from the expected distribution when we reject the null hypothesis.
<h3>What is a null hypothesis?</h3>
The null hypothesis exists as a specific mathematical theory that claims that there exists no statistical relationship and significance between two sets of observed data and estimated phenomena for each set of selected, single observable variables. The null hypothesis can be estimated to define whether or not there exists a relationship between two measured phenomena, which creates it useful. It can let the user comprehend if the outcomes exist as the product of random events or intentional manipulation of a phenomenon.
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Answer:
The correct option is (c).
Step-by-step explanation:
The assumptions of a two-sample <em>t</em>-test are:
- Independent samples
- Normality
- Equal variances
It is provided that the sample of selected for American adults under the age of 40 is of size, <em>n</em>₁ = 488 and the sample of selected for American adults aged 40 or over is of size, <em>n</em>₂ = 421.
As the sample size is quite large the according to the Central limit theorem the sampling distribution of the sample mean would follow a Normal distribution.
And even if the sample was selected by dialing of various telephone numbers, the sample is not biased since the size of the sample is too large.
So, the sample can be considered as a simple random sample.
Thus, the conditions for two-sample t inference are satisfied.
The correct option is (c).
let's recall that an inverse function has the same pair of coordinates as the original function, but backwards, or namely the inverse's range is the original's domain.
Step-by-step explanation:
distance = 160mile
time =5 hour or 5×60=300 minutes
speed =distance /time
v=160/300
v=0.5334miles per minute
