S = n(a1 + an)/2
2S = n(a1 + an)
2S = na1 + nan
nan = 2S - na1
an = (2S - n a1)/n
Answer:
bivariate data
Scatter plot
positive assossiation
negitive assossiation
linear assocciation
nonlinear assocciaton
clustering
outlier
Step-by-step explanation:
Answer:
NO
Step-by-step explanation:
The changeability of a sampling distribution is measured by its variance or its standard deviation. The changeability of a sampling distribution depends on three factors:
- N: The number of observations in the population.
- n: The number of observations in the sample.
- The way that the random sample is chosen.
We know the following about the sampling distribution of the mean. The mean of the sampling distribution (μ_x) is equal to the mean of the population (μ). And the standard error of the sampling distribution (σ_x) is determined by the standard deviation of the population (σ), the population size (N), and the sample size (n). That is
μ_x=p
σ_x== [ σ / sqrt(n) ] * sqrt[ (N - n ) / (N - 1) ]
In the standard error formula, the factor sqrt[ (N - n ) / (N - 1) ] is called the finite population correction. When the population size is very large relative to the sample size, the finite population correction is approximately equal to one; and the standard error formula can be approximated by:
σ_x = σ / sqrt(n).
Answer: Its a function
Step-by-step explanation:
