Abstract
In this paper, Team A will be determining and discussing how there will be an overall shortage of truck drivers in the years of 2012 and 2014. We will be using a null hypothesis and alternative hypothesis to determine which hypothesis is correct. The subject that is being testing is the issue of a possible decrease in the number of truck drivers that are present on our roads today.

A hypothesis test is being conducted to test the shortage of truck drivers in the coming years. Within the past years, the trucking industry has seen a decrease in the number of drivers on the road. This is due in part to the economy as well as the many regulations that are placed upon the industry (Beard, 2011). These regulations include the number of hours that truck driver is able to drive as well as the number of potential drivers who are unable to pass the mandated drug testing and if these potential drivers have a DUI (driving under the influence) within the past five to 10 years. Another reason for the shortage is that many of the younger population in the job force are seeking employment in the technology business; leaving an older population who is in this field who will retire in the approaching years. With these issues at hand, we can now look at the changes and how this will affect the hypothesis that is stated below. Five Step Hypothesis Testing Process

Data:
Year| CPS Estimate of # of Truck Drivers|
1994| 129,000|
1995| 131,000|
1996| 136,000|
1997| 146,000|
1998| 147,000|
1999| 147,500|
2000| 152,000|
2001| 151,000|
2002| 152,500|
(Beard, 2011)
Hypothesis 1: Stating the research question:
There is an overall shortage of truck drivers as the years 2012 and 2014 approach. It is said that the average shortage is from 1.4% to 0.5% per year. Using a significance level of 0.05 we are testing the claim whether the shortage of truck drivers in the year 2012...

...
HypothesisTestingPaper
Team A
PSY/315
July 7, 2014
Instructor: Regina Pendergrass
Inside statistics, it has to be understood what hypothesistesting is to find and verify research to be studied. Hypothesistesting is a form of research that is used to show how a certain issue will end or how the researcher(s) think the issue will end in the environment that it is situated. The testing will show that even though an answer may form, it does not prove the answer is correct secondary to the fact that there can me many factors that could change the outcome; this is where researchers can use probability rates of five or one percent. In understanding hypothesistesting, it must be known what the difference between null and research hypothesis means. A null hypothesis attempts to show that there is no variation between variables or that a single variable is actually no different from zero. A null hypothesis is what the researcher attempts to disprove, reject, or nullify. The research hypothesis is the specific testable predictions made about the independent and dependent variables inside the study. With the research hypothesis, it matches what the researcher(s) is attempting to prove true inside the problem or issue.
Hypothesis...

...APP6JMaloney problems 2. 4, 6, 10, 18, 22, 24
2 ) The value of the z score un a hypothesis test is influenced by a variety of factors.
Assuming that all the other variables are held constant, explain how the value
of Z is influenced by each of the following?
Z= M - u / SD
a) Increasing the difference between the sample mean and the original.
The z score represents the distance of each X or score from the mean.
If the distance between the sample mean and the population mean the z score will
increase.
b) Increasing the population standard deviation.
The standard deviation is the factor that is used to divide by in the equation. the bigger the SD,
then the smaller the z score.
c) Increasing the number of scores in the sample.
Should bring the samples mean closer to the population mean so z score will get smaller.
4) If the alpha level is changed from .05 to .01
a) what happens to the boundaries for the critical region?
It reduces the power of the test to prove the hypothesis.
You increase the chance of rejecting a true H
b) what happens to the probability of a type 1 error?
Type 1 error is falsely reporting a hypothesis,
Where you increase the chance that you will reject a true null hypothesis.
6) A researcher is investigating the effectiveness of a new study skills training program for elementary
school childreen. A sample of n=25 third grade children is selected to...

...HypothesisTesting For a Population Mean
The Idea of HypothesisTesting
Suppose we want to show that only children have an average higher cholesterol level than the national average. It is known that the mean cholesterol level for all Americans is 190. Construct the relevant hypothesis test:
H0: = 190
H1: > 190
We test 100 only children and find that
x = 198
and suppose we know the population standard deviation
= 15.
Do we have evidence to suggest that only children have an average higher cholesterol level than the national average? We have
z is called the test statistic.
Since z is so high, the probability that Ho is true is so small that we decide to reject H0 and accept H1. Therefore, we can conclude that only children have a higher average cholesterol level than the national average.
Rejection Regions
Suppose that = .05. We can draw the appropriate picture and find the z score for -.025 and .025. We call the outside regions the rejection regions.
We call the blue areas the rejection region since if the value of z falls in these regions, we can say that the null hypothesis is very unlikely so we can reject the null hypothesis
Example
50 smokers were questioned about the number of hours they sleep each day. We want to test the hypothesis that the smokers need less...

...all, the video did a fair job buttressing my understanding of hypothesistesting. The textbook explained the aspects and steps of hypothesistesting in a legible fashion, while the video helped demonstrate a real-life application.
I learned from the text that hypothesistesting is a “Procedure for deciding whether the outcome of a study (results from a sample) supports a particular theory or practical innovation (which is thought to apply to a population)” (Aron A., Aron, E., and Coups, 2011, p. 145). I also learned that hypothesistesting follows a set procedure that appears as follows:
Step 1) Restate the question as a research hypothesis and a null hypothesis about the populations
- Basically, a researcher constructs a hypothesis. Then he/she forms a null hypothesis that opposes the research hypothesis in
polar fashion. To help support one’s research hypothesis, one has to disprove the null hypothesis.
Step 2) Determine the characteristics of the comparison distribution
- When using two or more samples, one must gather information about the distribution of means.
Step 3) Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected
- Most researchers...

...United States is at an all-time high. The recession of the U.S. economy only hinders people more with high gas prices. A one population test using the One Factor ANOVA test and a five-step hypothesis test can be used to determine if gas prices are equally high in many different states. The samples used to test the hypothesis come from data collected from 30 randomly selected gas stations in six different cities. The hypothesis test and some solutions to consider may have an effect on direct and indirect stakeholders and is very important to the economy as a whole.
Data Points
Utah Virginia California Indiana Florida Virginia
Salt Lake city Wytheville Los Angeles Schererville Milton Richmond
Tina Sheri Jean Jennifer Kim Janet
3.33 3.42 3.85 3.79 3.65 3.37
3.34 3.44 3.83 3.83 3.65 3.59
3.35 3.51 3.79 3.79 3.63 3.41
3.54 3.48 3.79 3.85 3.68 3.49
3.61 3.55 3.89 3.74 3.67 3.46
Background
The purpose of this research is to identify trends and differences in gas prices in various regions of the United States. Gas prices vary across the country, and continually rise and fall, trending as the economy improves and worsens. The increase and decrease of gas prices depend on how well the economy is at the time, and can affect each of its stakeholders differently. The hypothesis is that gas prices, although they vary across the nation, will remain fairly equal in many different regions of the United...

...Lesson note #
Statistical Inference
Testing of Hypothesis
Type I Error:
Rejection of the null hypothesis when it is true is called a type I error.
Type II Error:
Acceptance of the null hypothesis when it is false is called a type II error.
|Decision of the test for the Null Hypothesis |The Null Hypothesis is |
| |True |False |
|Accept |Correct decision |Incorrect decision |
| | |Type II Error |
|Reject |Incorrect decision |Correct decision |
| |.Type I Error | |
Test Concerning Mean
One and Two tailed Tests:
A test procedure is called a one tailed test procedure if the alternative hypothesis is one sided. The test will be two tailed if the alternative hypothesis is two sided.
Example:
Let a specified value of population mean is 45. Construct the null and alternative hypothesis for the following questions;
a) Do the sample data provide...

...Simple Hypothesis: A statistical hypothesis which specifies the population completely (i.e. the form of probability distribution and all parameters are known) is called a simple hypothesis.
1. Composite Hypothesis: A statistical hypothesis which does not specify the population completely (i.e. either the form of probability distribution or some parameters remain unknown) is called a CompositeHypothesis.
HypothesisTesting or Test of Hypothesis or Test of Significance
HypothesisTesting is a process of making a decision on whether to accept or reject an assumption about the population parameter on the basis of sample information at a given level of significance.
Null Hypothesis: Null hypothesis is the assumption which we wish to test and whose validity is tested for possible rejection on the basis of sample information.
It asserts that there is no significant difference between the sample statistic (e.g. Mean, Standard Deviation(S), and Proportion of sample (p)) and population parameter (e.g. Mean(µ), standard deviation (σ), Proportion of Population (P)).
Symbol-It is denoted by Ho
Acceptance- The acceptance of null hypothesis implies that we have no evidence to believe otherwise and indicates that the difference is not significant.
Rejection- The...

...What is HypothesisTesting?
A statistical hypothesis is an assumption about a population parameter. This assumption may or may not be true. Hypothesistesting refers to the formal procedures used by statisticians to accept or reject statistical hypotheses.
Statistical Hypotheses
Null hypothesis. The null hypothesis, denoted by H0, is usually the hypothesis that sample observations result purely from chance.
Alternative hypothesis. The alternative hypothesis, denoted by H1 or Ha, is the hypothesis that sample observations are influenced by some non-random cause.
Hypothesis Tests
Statisticians follow a formal process to determine whether to reject a null hypothesis, based on sample data. This process, called hypothesistesting, consists of four steps.
State the hypotheses. This involves stating the null and alternative hypotheses. The hypotheses are stated in such a way that they are mutually exclusive. That is, if one is true, the other must be false.
Formulate an analysis plan. The analysis plan describes how to use sample data to evaluate the null hypothesis. The evaluation often focuses around a single test statistic.
Analyze sample data. Find the value of the test statistic (mean score, proportion, t-score, z-score, etc.) described in the...