Stanley Yeung
Results and Discussion
Biology Lab 017
04/02/12
Marigold Lab
The Purpose of this was to analyze how the Marigold plants grew under certain conditions. The Objective was to determine the amount of growth these plants went through by measuring the changes in the selected variables. The Variables that we selected were stem length, root length, the amount of leaves that grew on a plant and the overall size of the plant measured in height. For this experiment, we had three test groups, the first two groups had five seeds and the third group has 10 seeds. The reason for that is because we introduce the third group to interspecific competition. We wanted to find out if variables such as competition will have an effect on the plants development. We hypothesized that the group with the most seeds will see the least development and growth due to competition. We calculated out results and they are as follows. The TCritial is constant at 2.23. The growth of the leaves was higher in the low density group as opposed to the high density group. The T-Stat is 5.17 for the stems 1.87 for the height, .285 for the leaves and .11 for the roots. Both the low and the high density variables share the same T-Stat. This simply means that the plant group with the least amount of competition has a higher chance at achieving reproductive success. Some of the plants in the third group with 10 seedlings did not even grow. With that said, we reject the null hypothesis and accept the alternative because some of the plants in the pot with the larger amount of seeds did not even start to grow. All of the plants in the groups with 5 seeds at least grew. This indicates that dependent variables such as competition and the environment itself has an influence on how a plant grows and develops. If the T-Stat>T-Critical, then we reject the null hypothesis and choose the alternative. The only one we actually accept the null hypothesis are the Leaves and the Roots...

...Chapter-11
Testing of Hypothesis:
(Non-parametric Tests)
Chapter-11: Testing of Hypothesis - (Non-parametric Tests)
2
11.1. Chi - square ( χ )Test / Distribution
2
11.1.1. Meaning of Chi - square ( χ )Test
2
11.1.2. Characteristics of Chi - square ( χ )Test
2
11.2. Types of Chi - square ( χ )Test / Distribution
2
11.2.1. Chi - square ( χ )Test for Population Variance
2
11.2.2. Chi - square ( χ )Test for Goodness-of-Fit
2
11.2.3. Chi - square ( χ )Test or Independence
11.3. Analysis of Variance (ANOVA)
11.3.1. Meaning of ANOVA
11.3.2. ANOVA Approach
11.4. ANOVA Technique
11.4.1. One-way ANOVA
11.4.2. Two-way ANOVA
11.4.3. ANOVA in Latin-square Design
11.5. Other Nonparametric Techniques
Summary:
Key Terms:
Questions:
11.1. CHI-SQUARE (
) TEST /DISTRIBUTION
2
11.1.1. Meaning of Chi - square ( χ )Test
2
A chi-square test (also chi squared test or χ test) is any statistical hypothesis test in which the
sampling distribution of the test statistic is a chi-square distribution when the null hypothesis is true,
or any in which this is asymptotically true, meaning that the sampling distribution (if the null
hypothesis is true) can be made to approximate a chi-square distribution as closely as desired by
making the sample size large enough. The Chi-Square (
) test is the most popular non-parametric
test/methods, to test the hypothesis. The...

...
The word ‘Hypothesis is derived from a Greek word, which means ‘to suppose’. It is usually considered as the principal instrument in research. For a researcher it is a formal question that he or she intends to resolve. In this way a hypothesis may be defined as a proposition or a supposition. The main function of hypothesis is to guide the collection and processing of materials and direct the research. Hypothesis is a tentative conclusion. It is facts based theory. A research scholar will analyze the information from variety of sources in order to create a hypothesis. Hypothesis can be of two types –
- Explanatory
- Descriptive
In explanatory hypothesis researcher tries to account for a given fact and the explanation is provisional because it is based on inconclusive proof. This method is especially used in finding out laws in history. The defeat of the army of Siraj in the battle of Plassey is a fact. Various explanations are offered for this fact. Again the rise of Gandhi has been accounted for variously by various authors such as Shaid Amin and Judith Brown. These explanations are really the nature of hypothesis.
Descriptive hypothesis is employed for making a complex mass of facts, which are isolated from one another, a meaningful unit by describing it in a collective manner. To...

...CHAPTER
7
THE TWO-VARIABLE REGRESSION MODEL:
HYPOTHESIS TESTING
QUESTIONS
7.1. (a) In the regression context, the method of least squares estimates the regression parameters in such a way that the sum of the squared difference between the actual Y values (i.e., the values of the dependent variable) and the estimated Y values is as small as possible.
(b) The estimators of the regression parameters obtained by the method of least squares.
(c) An estimator being a random variable, its variance, like the variance of any random variable, measures the spread of the estimated values around the mean value of the estimator.
(d) The (positive) square root value of the variance of an estimator.
(e) Equal variance.
(f) Unequal variance.
(g) Correlation between successive values of a random variable.
(h) In the regression context, TSS is the sum of squared difference between the individual and the mean value of the dependent variable Y, namely, [pic].
(i) ESS is the part of the TSS that is explained by the explanatory variable(s).
(j) RSS is the part of the TSS that is not explained by the explanatory variable(s), the X variable(s).
(k) It measures the proportion of the total variation in Y explained by the explanatory...

...Why We Don’t “Accept” the Null Hypothesis
by Keith M. Bower, M.S. and James A. Colton, M.S.
Reprinted with permission from the American Society for Quality
When performing statistical hypothesis tests such as a one-sample t-test or the AndersonDarling test for normality, an investigator will either reject or fail to reject the null
hypothesis, based upon sampled data. Frequently, results in Six Sigma projects contain
the verbiage “accept the null hypothesis,” which implies that the null hypothesis has been
proven true. This article discusses why such a practice is incorrect, and why this issue is
more than a matter of semantics.
Overview of Hypothesis Testing
In a statistical hypothesis test, two hypotheses are evaluated: the null (H0) and the
alternative (H1). The null hypothesis is assumed true until proven otherwise. If the
weight of evidence leads us to believe that the null hypothesis is highly unlikely (based
upon probability theory), then we have a statistical basis upon which we may reject the
null hypothesis.
A common misconception is that statistical hypothesis tests are designed to select the
more likely of two hypotheses. Rather, a test will stay with the null hypothesis until
enough evidence (data) appears to support the alternative.
The amount of evidence required to “prove”...

...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...

...Read step 2: The hypothesis
Answer the following questions:
* What is a hypothesis?
* How is a hypothesis different from a theory in science?
* Describe an example of how you may use the scientific method in your daily life and state a good hypothesis for that example.
* Which hypothesis did you first pick in the "Recognizing a good hypothesis" activity in the scientific method tutorial? Why? If any, which mistake(s) did you make when picking a hypothesis?
A hypothesis is a specific possible explanation for a particular observation or phenomenon, or a logical guess about how things work. In addition, hypothesis is testable as well as falsifiable through experimentations or investigations. Theory in the other hand is much broader, well tested and has not been falsified, it is also well accepted by the general compare to hypothesis. One example on how the scientific method is used in my daily life is when my cell phone randomly dies or turns off. I attempted to turn it on but it wouldn’t. So now, I come up with a hypothesis that my cell phone died due to the battery is out of power.
On the activity “Recognizing Good Hypothesis”, I have chosen the second statement “B. E. coli cells will die within 8 hours if it is exposed to temperatures below 80˚F.” because the statement provided...

...Alyazia Juma Al Muhairi
201013709
Communication research methods (52)
Null Hypothesis
The null hypothesis, is an essential part of any research design, and is always tested, even indirectly. The 'null' often refers to the common view of something, and so the null hypothesis (H0) is a hypothesis in which the researcher tries to disprove, reject or nullify.
Examples of the Null Hypothesis
A researcher may postulate ahypothesis:
H1: Tomato plants exhibit a higher rate of growth when planted in compost rather than in soil.
And a null hypothesis:
H0: Tomato plants do not exhibit a higher rate of growth when planted in compost rather than soil.
It is important to carefully select the wording of the null, and ensure that it is as specific as possible. For example, the researcher might postulate a null hypothesis:
H0: Tomato plants show no difference in growth rates when planted in compost rather than soil.
There is a major flaw with this H0. If the plants actually grow more slowly in compost than in soil, an impasse is reached. H1 is not supported, but neither is H0, because there is a difference in growth rates.
If the null is rejected, with no alternative, the experiment may be invalid. This is the reason why science uses a battery of deductive and inductive processes to ensure that there are no flaws in the hypotheses.
Resources:...

...Real Estate Sample Hypothesis Testing
The question or issue that the buyer wants to address is that property closer to town is more expensive so buyers that purchase property further from the center of town get a more affordable home. The research is necessary so that the buyer will remain within the budget that they have set for themselves. Although the cost of the home is very important, it is also important to factor in other expenditures such as upkeep, repairs and any upgrades that may want to be added. It is a critical move for the buyer to factor in all the expenses incurred in the move. The buyer may also want to be aware that the property in the center of town as well as the property outside the center of town will have different taxes depending on the township or county they are in. To begin the buying process, the buyer must research the area in which he or she would like to buy property.
When purchasing a home, location is everything. As a buyer, one should be aware of the cost of living in the area of choice, as well as expect a higher cost the closer to the center of town you get. It is also important as a buyer to find an area that fits your lifestyle as well as your budget. Many working families require both parents to travel to a metropolis area for work but feel that the city is not a place to raise a child and that the suburbs may be more suitable.
However, they must factor in the extra expenditures that will be spent on the...

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