Hope you do well on your final, Christina, and find what you're looking for. Quare should be able to help you, so you can PM him. Or if you want to discuss here, or PM me, you can do that. I work in Finance, and did quite a few statistics courses in college, including Hypothesis testing that you asked about.

I frequently used statistical tests in my last role. So I'll be happy to help if I can.

Hypothesis Testing can be confusing. Different books will give you different approaches. Imho, you can choose which suits you if you know what we are basically trying to check: you could follow this. (1) State the Null and Alternate Hypothesis. (2) For your given Alpha Level (Significance Level=1-Confidence Level), find the value of Z from the tables (3) Compute Z using the formula, this is your calculated Z score which you will compare with the tabulated value. The tabulated values give you the range in which the Null hypothesis can be accepted, or is not rejected. If the calculate value is outside that range, you reject the null hypothesis.

The explanation given here is decent:

http://www.statisticshowto.com/probability-and-statistics/hypothesis-testing/Or, if you don't want to memorize too many formulas, use the data given in the question. Let's take an example from the link. We will assume they are equal and then see if we have data to reject that and prove the opposite.

"A principal at a certain school claims that the students in his school are above average intelligence. A random sample of thirty students IQ scores have a mean score of 112. Is there sufficient evidence to support the principal’s claim? The mean population IQ is 100 with a standard deviation of 15."

Step 1: Find the difference between Sample and Population Mean. (SM-PM)=112-100=12 [This is the main difference or deviation you're checking]

Step 2: Standardize this difference by Sample Standard Deviation. 12/(15/sqrt(30)>4 [You can imagine this as a standardized difference to check for]

Step 3: Cross check with values for 5% Significance Level,=1.645. [This value is from the Normal Distribution Tables. Mainly the 5% or 1% level will be asked]

Therefore, you can confidently say 112 is significantly greater from 100, and the hypothesis of equivalence is to be rejected. With 95% level of confidence, it can be stated that the IQ in that school is indeed above average. Did that make sense? Was the limited explanation helpful?