(a) Breaking down a project into manageable jobs, work packages or activities falls under project time management in project management. Activities are firstly defined, sequenced, resources required estimated, the duration estimated, schedule developed and finally control the schedule. As noted earlier, these processes form project time management. It can be argued that successful project management depends on the ability of the project manager to breakdown a project into manageable activities so that everything becomes decomposed, clear and simplified. However, breaking down a project into manageable jobs or activities cannot be entirely said to be the success of projects. Project management involves other process or knowledge areas like scope management, cost management, risk management among others which work together as the nine knowledge areas for the success of any project. As a project manager, it is critical to breakdown any given project into manageable jobs, work packages or activities. An activity can be noted as an action taken in pursuit of a project objective. It is from the activities that a project can be visible, what needs to be done and makes easy to measure progress, celebrate milestones in order to reach objectives and finally the intended goal. Therefore a project manager should have the required skills in time management for the success of any project. In breaking down a project into activities, a project manager needs to firstly define the activity or activities. This process involves identifying the specific actions to be performed to produce the project deliverable. It can be argued that this stage or process is critical because every work to follow thereafter follows this process. For instance if it is building a shopping complex like Joina City as the project, the specific actions to be performed had to be identified and clear like applying for the stand, architectural drawings and plans, digging the foundation, erecting the slab inter...

...Testing statistical significance is an excellent way to identify probably relevance between a total data set mean/sigma and a smaller sample data set mean/sigma, otherwise known as a population mean/sigma and sample data set mean/sigma. This classification of testing is also very useful in proving probable relevance between data samples. Although testing statistical significance is not a 100% fool proof, if testing to the 95% probability on two data sets the statistical probability is .25% chance that the results of the two samplings was due to chance. When testing at this level of probability and with a data set size that is big enough, a level of certainty can be created to help determine if further investigation is warranted. The following is a problem is used to illustrate how testing statistical significance paints a more descriptive picture of data set relationships.
Sam Sleep researcher hypothesizes that people who are allowed to sleep for only four hours will score significantly lower than people who are allowed to sleep for eight hours on a management ability test. He brings sixteen participants into his sleep lab and randomly assigns them to one of two groups. In one group he has participants sleep for eight hours and in the other group he has them sleep for four. The next morning he administers the SMAT (Sam's Management Ability Test) to all participants. (Scores on the SMAT range from 1-9 with high scores...

...reproduces it reproduces in large quantities. Also it is a model organism because so much is already known about it. The Drosophila egg is about half a millimeter long. One day after fertilization the embryo develops and hatches worm like larvae. The larva continuously eats and grows, and moults four times. The fourth time it moults it forms an immobile pupa and turns into the winged form. It hatches in about 4 days and is fertile in 12 hours.
Statistical analysis can be used to determine if there is a significant difference between two of group data sets. One way to do this is to use a Chi square. The Chi square test produces a number which you compare to a statistical Chi square number. Each of these statistical numbers has a significance level. Significance levels show you how likely a result is due to chance. The most common level, which is also used in this lab, is .95 which makes something good enough to be believed. This means that 95% of the time the findings will be true, and 5% of the time they will not. If the Chi square produces a number which is less then the statistical value, you accept your null hypothesis, meaning that there is no significant difference between the data. If the Chi square test produces a number higher than the statistical value then you must refute your null hypothesis, meaning that there is a significant difference in your data. The null hypothesis used is that the pattern for inheritance is autosomal. The...

...Psychology 1983, Vol. 30, No, 3,459-463
Copyright 1983 by the American Psychological Association, Inc.
Statistical Significance, Power, and Effect Size: A Response to the Reexamination of Reviewer Bias
Bruce E. Wampold
Department of Educational Psychology University of Utah
Michael J. Furlong and Donald R. Atkinson
Graduate School of Education University of California, Santa Barbara
In responding to our study of the influence that statisticalsignificance has on reviewers' recommendations for the acceptance or rejection of a manuscript for publication (Atkinson, Furlong, & Wampold, 1982), Fagley and McKinney (1983) argue that reviewers were justified in rejecting the bogus study when nonsignificant results were reported due to what Fagley and McKinney indicate is the low power of the bogus study. The concept of power is discussed in the present article to show that the bogus study actually had adequate power to detect a large experimental effect and that attempts to design studies sensitive to small experimental effects are typically impractical for counseling research when complex designs are used. In addition, it is argued that the power of the bogus study compares favorably to that of research published in the Journal of Counseling Psychology at the time our study was completed. Finally, the importance of considering statistical significance, power, and effect size in the evaluation of research findings is...

...Significance of the study
This section will provide brief description on the various significances of the study. The primordial purpose of the study is to provide the students with a complete and balance education by avoiding peer pressure. Thus, the results of this study will benefit the students, the school administrators, the teachers not only in English but also in other subjects, and especially the parents who are concerned about the behavior of their children.
This study will serve as the basis for future plans of actions by the school administrators or few psychiatrists with regard to the necessary actions for the recovery of the deteriorating moral values of the students.
To students, the proposed study serves the students as their references guide in avoiding peer pressure. It will also help students to build self-esteem and confidence in one’s own abilities and actions, by following the 5 ways to avoid peer pressure.
To parents, the proposed study serves the parents as their reference guide to avoid the negative effects of peer pressure. It will also help the parents to scold their children more easily. In order to help their children parents should consider warm parenting with strict boundaries, and by following the 5 ways to avoid peer pressure.
Furthermore, this study will serves as a model for future researchers of the same nature if ever the existing problem has penetrated in this case will exist in the future. Future...

...Homework Exercise 29
Grand Canyon University
December 23, 2012
1. Were the groups in this study independent or dependent? Provide a rationale for your answer. Answer- The group studies were independent. They were being tested by gender, male and female. They were also not matched or paired with each other.
2. t = −3.15 describes the difference between women and men for what variable in this study? Is this value significant? Provide a rationale for your answer. Answer- The variable that is described by -3.15 is the mental health variable. It is significant as indicated by the p value of 0.002. This is less than the alpha number of 0.05
3. Is t = −1.99 significant? Provide a rationale for your answer. Discuss the meaning of this result in this study. Answer- The variable that -1.99 is for is health functioning. It is significant. The p is 0.049. Since the p value is less than the alpha of 0.05 that was designated for the test. The women have lower health functioning than the men have.
4. Examine the t ratios in table VI. Which t ratio indicates the largest difference between male and females in the post MI study? Is this t ratio significant? Provide a rationale for your answer. Answer- The largest t ratio in this study is -3.15 this has a p value of 0.002. It is for the variable of mental health. It is significant. The means are 62.3 for women and 72.7 for men. There is a big difference between the two genders.
5. Consider t =...

...Frederick Jackson Turner, The Significance of the Frontier in American History
*-* Turner, "The existence of an area of free land, its continuous recession, and the advance of American settlement westward explain American development."
-The census of 1890 said that the frontier line by 1880 was indiscernible. Turner considered that vital since the official American history up 2 that time consisted of the colonization of the West& that it was this that explained American development.-The West compelled ppl to adapt themselves& 2 developing each area out of its primitive economic/political conditions. - Its isolation led to the need of transportation.
-The American frontier is distinct from the European frontier due 2 an abundance of free land. Its isolation led to the need of transportation.
-Although the frontier forced ppl to change (switch from railroad car to canoe) it still maintains frontier characteristics after being settled. Thus, the frontier meant a steady movement away form the influence of Europe.
-The areas that had been settled upon were a source of political concern since it was surrounded by Indians.
-The frontier led to trade between Indians& whites. I.e. astor's American Fur co. operated in the Indian trade.
-The need to expand is inherent in Americans (Erie Canal, extension of cotton culture).
-California(gold rush) was a distinctive frontier. Now settlers needed means of communication w/the East.
-Railroads (aided by land grants)...

...Sample Outline for Review, Gap, Purpose, Significance and Scope
1.3.1 The Numerical Approach
… (omitted review of earlier studies)
Modified Smith’s model incorporating Novak’s theoretical solution -Simon & Randolph (1985), Wong (1988)
different definitions of ultimate failure – assumptions
difference in result – insignificant
Discrepancy - measured & simulated radiation damping effect - cause (Nogami & Konagai, 1986)
Deal with discrepancy - include shear zone - Novak & Sheta, 1994
[Summary/Comments]
All models able to simulate pile dynamic response
Simulate soil nail dynamic pullout response-uncertain: assumption vs reality
1.3.2 Experimental Approach
[Link to section 1.3.1] Models require pre-determination of ultimate failure behavior
need guideline on determination of ultimate dynamic interfacial strength
experimental work on relationship betw ultimate soil strength & loading freq
Coyle & Gibson (1970)– triaxial condition, sample, results
Comment –why results may not explain soil nail dynamic pullout response
Heerema (1979) – modifications to Coly & Gibson’s, results
Comment –No restraint dilatancy effect, no load displacement response
Dayal and Allen (1975) & Litkouhi and Poskiti (1980) –on pile driven rate
No direct assessment on friction. No base resistance, rely on interfacial res
Different mechanisms in compression& tension test (Nicola & Randolph,1993)
Randolph (1998) interfacial resistance in compression test - 30% higher...

...
Abstract
Power Analysis, Statistical Significance, & Effect Size
“If you plan to use inferential statistics (e.g., t-tests, ANOVA, etc.) to analyze your evaluation results, you should first conduct a power analysis to control what size sample you will need. Statistical tests look for evidence that you can reject the null hypothesis and conclude that your program had an effect. With any statistical test, however, there is always the possibility that you will find a difference between groups when one does not actually exist. This is called a Type I error. Likewise, it is possible that when a difference does exist, the test will not be able to identify it. This type of mistake is called a Type II error”. (merra.snr.umich.edu)
Statistical Tests
The two variables measure assorted arrangements of the students that had anxiety marks and study hours it is more appropriate to conduct the correlation examination than other investigation. Null hypothesis be made up of there is no correlation between the study of anxiety scores and the study hours. (Or r is not equal to 0) If the alpha was set at 0.05, this is will be a two tailed t test. The degree of freedom 10 – 2 = 8, the critical t causes are +/- 2.306. The correlation coefficient r = 0.5654. Test value (effect size) =r square ((n-2) / (1-r^2)) = 0.5654* square root ((10-2) / (1-0.5654^2)) =1.939. Therefore since 1.939 < 2.306, we could not reject the null hypothesis. Based on the...