Stepwise Descriptive Statistics Learning

I am looking at Central Limit Theorem. It says that for a series of random sample $W_1,\cdots <!--\; \cdots \; -->,W_2$ under the same mean $\mathrm{\mu <!--\; \mu \; -->}$ and standard deviation $\mathrm{\sigma <!--\; \sigma \; -->}$, then the random variable
${\displaystyle \frac{\stackrel{¯<!--\; ¯\; -->}{W}-<!--\; -\; -->\mathrm{\mu <!--\; \mu \; -->}}{\mathrm{\sigma <!--\; \sigma \; -->}/\sqrt{n}}}$
follows normal distribution. However, it seems like for Binomial samples,
${\displaystyle \frac{\stackrel{¯<!--\; ¯\; -->}{W}-<!--\; -\; -->\mathrm{\mu <!--\; \mu \; -->}}{\mathrm{\sigma <!--\; \sigma \; -->}}}={\displaystyle \frac{\stackrel{¯<!--\; ¯\; -->}{W}-<!--\; -\; -->np}{\sqrt{np(1-<!--\; -\; -->p)}}}$
is normal. I want to know where the n−−√ term in the denominator went?

Find all solutions of $z^2+{\stackrel{¯<!--\; ¯\; -->}{z}}^2=0$
How do I solve this equation? Also plotting all these solutions on the graph needed.
$z^2+{\stackrel{¯<!--\; ¯\; -->}{z}}^2=0$
I have got something like
$(x+iy{)}^2=\sqrt{-<!--\; -\; -->(x-<!--\; -\; -->iy{)}^2}$
$x+iy=y+ix$

Which of the following statements about effect size is true?
$\mathrm{◻<!--\; ◻\; -->}$ A larger difference between the population means leads to a smaller effect size.
$\mathrm{◻<!--\; ◻\; -->}$ Sample size (n) does not change the effect size.
$\mathrm{◻<!--\; ◻\; -->}$ A larger sample leads to a smaller effect size.
$\mathrm{◻<!--\; ◻\; -->}$ The difference between the populations means does not change the effect size.

Describe exactly what information is provided by a z-score. A positively skewed distribution has $\mathrm{\mu <!--\; \mu \; -->}=80,\mathrm{\sigma <!--\; \sigma \; -->}=12$. If this entire distribution is transformed into z-scores, describe the shape, mean, and standard deviation for the resulting distribution of z-scores.

Interpret a Cohen's d of 42.83

If G is a bipartite Euler and Hamiltonian graph, prove that complement of G, $\stackrel{¯<!--\; ¯\; -->}{G}$ is not Eulers.
I would like to know if my proof of the statement in the title is correct.
So, I started like this:
As G is a bipartite graph, it has two sets X and Y. Using the condition G is Hamiltonian, then |X|=|Y|.
As G is also Eulerian, stands $d_G(v)$ is even $\mathrm{\forall <!--\; \forall \; -->}v\in <!--\; \in \; -->V(G)$, where V(G) is set of vertices of the graph G.
Now, let's look at some vertex $v\in <!--\; \in \; -->X(G)$. As stated above, it's degree is even. Let's look at two possible cases:
If |X|=|Y| is even too, then in $\stackrel{¯<!--\; ¯\; -->}{G}$, v will be connected with all the remaining vertices from X. That vertex v will also be connected with remaining vertices from Y, with which it wasn't connected in the graph G. That is, $d_{\stackrel{¯<!--\; ¯\; -->}{G}}(v)=|X|-<!--\; -\; -->1+m$, where m represents number of remaining vertices from Y. As |X| is even, then |X|−1 is odd, and m is also even, because $d_{\stackrel{¯<!--\; ¯\; -->}{G}}(v)$ is even and |Y| is even, so the remaining number of vertices, m is even too. Sum of an even and an odd number is odd, so $d_{\stackrel{¯<!--\; ¯\; -->}{G}}(v)$ is odd. That means $\stackrel{¯<!--\; ¯\; -->}{G}$ is not Eulerian;
If $|X|=|Y|$ is odd, in $\stackrel{¯<!--\; ¯\; -->}{G}$, v will be connected with all the remaining vertices from X and all the remaining vertices from Y, and let's call the number of Y remaining vertices m. As $|Y|$ is odd and $d_G(v)$ is even, then m is odd. Degree of v in $\stackrel{¯<!--\; ¯\; -->}{G}$ is once again $d_{\stackrel{¯<!--\; ¯\; -->}{G}}(v)=|X|-<!--\; -\; -->1+m$, but this time $|X|-<!--\; -\; -->1$is even, and m is odd. $d_{\stackrel{¯<!--\; ¯\; -->}{G}}(v)$ is odd and that means $\stackrel{¯<!--\; ¯\; -->}{G}$ is not Eulerian.
Thank You!

I have a problem solving this exercise. I have this:
1. $P(0\le <!--\; \le \; -->Z\le <!--\; \le \; -->z_2)=0.3$
2. $P(Z\le <!--\; \le \; -->z_1)=0.3$
3. $P(z_1\le <!--\; \le \; -->Z\le <!--\; \le \; -->z_2)=0.8$
I need to find the z values for each given probability. I already solved the first and the second like this:
1. I calculated the inverse standard normal distribution (with LibreOffice Calc) and I found that $z_2$ is 0.841
2. I calculated the inverse standard normal distribution (with LibreOffice Calc) and I found that $z_1$ is −0.524
How can I find $z_1$ and $z_2$ of the third point of the exercise?

Which of the following best describes meta-analysis?
a. Evidenced-based practice.
b. A treatment versus no treatment group.
c. A tendency for smaller scores to move toward the average.
d. Regressing from unusual to usual. e. A way to combine the results of lots of studies.

1. What is meant by meta analysis? Find an article that has conducted a meta analysis. Send me the link to it.
2. Explain the advantage of having conducted a meta analysis in the study you selected.

How do you find the domain and range of $f(x)=e^{5x}$?

What is the z-score of sample X, if $n=54,\mathrm{\mu <!--\; \mu \; -->}=12,\text{St.Dev}=30,{\mathrm{\mu <!--\; \mu \; -->}}_X=11$?

Can a z-score be negative?

What is the z-score of sample X, if $n=36,\mathrm{\mu <!--\; \mu \; -->}=8,\text{St.Dev}=9,{\mathrm{\mu <!--\; \mu \; -->}}_X=11.2$?

How to calculate the interquartile range.

Z-scores are useful with regard to inferential statistics primarily because they offer a tool by which to determine whether _____.
a. an individual is different from a sample.
b. a sample is noticeably different from a population.
c. a distribution of scores is standardized.
d. a distribution of scores is symmetrically shaped.

How do you find the domain and range of $y=-<!--\; -\; -->3\sin <!--\; \; -->(\frac{1}{2})x$?

This describes the effect of a single variable as if there were no other variables in the study.
Use one of the following key terms to answer each of the following questions.
KEY TERM BANK (separated by commas):
Univariate, Multivariate, meta-analysis, F-ratio, interaction, main effect

Susan is 4' 11 tall (59 inches). Given that the average height for women is 63.5" and the standard deviation is 2.5", find Susan's z-score.
Hint: Z-score can be positive or negative. Make sure you determine which appropriately.

What is the range if f(x) =2x + 5 and domain: -1,0,3,7,10 ?