Mating Decisions Females And Females - 1388 Words

A number of factors play into the decision of one individual to mate with another, and in many species the females are the ones making these mating decisions. In terms of successfully reproducing, the number of offspring a male produces is limited by the number of females he gets to mate with, whereas females are limited by the amount of resources available to her. Thus, if males want to maximize the number of offspring they can produce they will choose to mate with those females who have access to the most resources and therefore are the most fertile. So, in a species dominated by male choice, research has suggested that males will tend to choose those females whose physical characteristics indicate high fertility. Those females who are†¦show more content†¦It had previously been found that male guppies preferred larger females, because body size correlates with the number of eggs she is capable of producing, and thus is an indicator of her fertility. As a result, male gupp ies transfer more sperm to larger females, because it increases their chances of fathering the most offspring. For a male to be interested in mating with a particular female, the benefits of mating with her must outweigh the costs. The benefit of mating with a larger female, as opposed to a smaller female, is that there are more eggs to fertilize, thus the male would have more offspring, and a higher reproductive success. On the other hand, the cost of mating with a larger female is the increase in sperm competition that he would face. With this in mind, Jeswiet et al. sought to determine if male guppies were simultaneously able to assess both size and sperm competition in choosing a mate, thereby increasing their reproductive success, and whether the benefit of successfully mating with a female of larger size outweighed the cost of having to compete with other males to mate with her. They hypothesized that male guppies who saw females interacting with another male, would be less li kely to pursue that female, and as the number of competing males increased, the male would become increasingly uninterested in that particular female because the costs of mating with her would outweigh the benefits. To test their hypotheses, adultShow MoreRelatedSexual Reproduction And Mating Systems Essay1567 Words   |  7 Pagesmates, in some cases with a lot of consideration. Mating systems are critical to comprehend in light of the fact that they mirror the consequence of common choice on mate decision, and eventually on systems for augmenting individual reproductive success. A mating system depicts how guys and females pair while picking a mate. Males and females vary extraordinarily in the speculation every makes to reproduce, and may along these lines approach mating with contrasting procedures. 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Statistics †Elements of a Test Hypothesis Free Essays

Elements of a Test of Hypothesis 1. Null Hypothesis (H0 ) – A statement about the values of population parameters which we accept until proven false. 2. We will write a custom essay sample on Statistics – Elements of a Test Hypothesis or any similar topic only for you Order Now Alternative or Research Hypothesis (Ha )- A statement that contradicts the null hypothesis. It represents researcher’s claim about the population parameters. This will be accepted only when data provides su? cient evidence to establish its truth. 3. Test Statistic – A sample statistic (often a formula) that is used to decide whether to reject H0 . 4. Rejection Region- It consists of all values of the test statistic for which H0 is rejected. This rejection region is selected in such a way that the probability of rejecting true H0 is equal to ? (a small number usually 0. 05). The value of ? is referred to as the level of signi? cance of the test. 5. Assumptions – Statements about the population(s) being sampled. 6. Calculation of the test statistic and conclusion- Reject H0 if the calculated value of the test statistic falls in the rejection region. Otherwise, do not reject H0 . 7. P-value or signi? cance probability is de? ned as proportion of samples that would be unfavourable to H0 (assuming H0 is true) if the observed sample is considered unfavourable to H0 . If the p-value is smaller than ? , then reject H0 . Remark: 1. If you ? x ? = 0. 05 for your test, then you are allowed to reject true null hypothesis 5% of the time in repeated application of your test rule. 2. If the p-value of a test is 0. 20 (say) and you reject H0 then, under your test rule, at least 20% of the time you would reject true null hypothesis. 1. Large sample (n 30) test for H0 :  µ =  µ0 (known). Z= x ?  µ0 ? ? v n Example. A study reported in the Journal of Occupational and Organizational Psychology investigated the relationship of employment status to mental health. Each of a sample of 49 unemployed men was given a mental health examination using the General Health Questionnaire (GHQ). The GHQ is widely recognized measure of present mental health , with lower values indicating better mental health. The mean and standard deviation of the GHQ scores were x = 10. 94 and s = 5. 10, ? respectively. (a). Specify the appropriate null and alternative hypothesis if we wish to test the research hypothesis that the mean GHQ score for all unemployed men exceeds 10. Is the test one-tailed or two-tailed? (b). If we specify ? = 0. 05, what is the appropriate rejection region for this test? c). Conduct the test, and state your conclusion clearly in the language of this exercise. Find the p-value of the test. (Ans. H0 :  µ = 10; Ha :  µ 10; One-tailed test; Rejection region: Z 1. 645; Test score: Z = 1. 29; Do not reject H0 , GHQ score does not exceeds 10; p-value = 0. 0985) Example. A consumer protection group is concerned that a ketchup manufacturer is ? lling its 20-ounce family-size containers with less than 20 ounces of ketchup. The group purchases 49 family-size bottles of this ketchup, weigh the contents of each, and ? nds that the mean weight is 19. 6 ounces, and the standard deviation is equal to 0. 22 ounces. (a). Do the data provide su? cient evidence for the consumer group to conclude that the mean ? ll per family-size bottle is les than 20 ounces? Test using ? = 0. 05. (b). Find the p-value of the your test in part (a). (Ans. H0 : = 20; Ha : 20; Rejection Region is Z ? 1. 645 (one-tailed test); test score Z = ? 4. 45; Reject H0 at ? = 0. 05, su? cient evidence to say that the mean ? ll per family-size bottle is less than 20 ounces; p-value = 0) Example. State University uses thousands of ? uorescent light bulbs each year. The brand of bulb it currently uses has a mean life of 900 hours. A manufacturer claims that its new brands of bulbs, which cost the same as the brand the university currently uses, has a mean life of more than 900 hours. The university has decided to purchase the new brand if, when tested, the test evidence supports the manufacturer’s claim at the . 10 signi? cance level. Suppose 99 bulbs were tested with the following results: x = 919 hours, s = 86 hours. Find the rejection region for the test of interest to the State University. ? (Ans. Rejection Region: Z 1. 28) 1 . Small sample (n ? 30) test for H0 :  µ =  µ0 (known). t= This test requires that the sampled population is normal. x ?  µ0 ? s v n Example. A random sample of n observations is selected from a normal population to test the null hypothesis that  µ = 10. Specify the rejection region for each of the following combinations of Ha , ? , and n. (a). Ha :  µ = 10, ? = 0. 01, n = 14. (Ans. t ? 3. 012, or t 3. 012) (b). Ha :  µ 10, ? = 0. 025, n = 26. (Ans. t ? 2. 06) Example. According to advertisements, a strain of soybeans planted on soil prepared with a speci? d fertilizer treatment has a mean yield of 475 bushels per acre. Twenty farmers who belong to a cooperative plant the soybeans. Each uses a 40-acre plot and records the mean yield per acre. The mean and variance for the sample of 20 farms are x = 462 and s2 = 9070. ? Specify the null and alternative hypothesis used to determine if the mean yield for the soybeans is di? erent than advertised. (Ans. H0 :  µ = 475; Ha :  µ = 475) Example. A psychologist was interested in knowing whether male heroin addicts’ assessments of self-worth di? er from those of the general male population. On a test designed to measure assessment of self-worth, the mean score for males from the general population was found to be equal to 48. 6. A random sample of 25 scores achieved by heroin addicts yielded a mean of 44. 1 and a standard deviation of 6. 2. Do the data indicate a di? erence in assessment of self-worth between male heroin addicts and general male population? Test using ? = 0. 01. (Ans. H0 :  µ = 48. 6; Ha :  µ = 48. 6; Test score t = ? 3. 63 Rejection Region: t 2. 797, or t ? 2. 797 (two-tailed test); Observed t-score falls in the rejection region. Reject H0 at ? = 0. 1. Data indicate a di? erence in assessment of self-worth between male heroin addicts and general male population) 3. Large sample test for H0 : p = p0 (known). Z= p ? p0 ? p0 (1? p0 ) n For this test, sample size is considered large if p0  ± 3 p0 (1? p0 ) n falls between 0 and 1. Example. The National Science Foundation, in a survey of 2,237 engineering graduate students who earned their Ph. D. deg rees, found that 607 were U. S. citizens; the majority (1,630) of the Ph. D degrees were awarded to foreign nationals. Conduct a test to determine whether the true percentage of engineering Ph. D. degrees awarded to foreign nationals exceeds 50%. Use ? = 0. 01. (Ans. H0 : p = 0. 5; Ha : p 0. 5; Test score Z = 21. 63; Rejection region; Z 2. 33 (one tailed test) Reject H0 at ? = 0. 01. True percentage p exceeds 50%. p-value = 0) Example. The business college computing center wants to determine the proportion of business students who have personal computers (PC’s) at home. If the proportion exceeds 30 percent, then the lab will scale back a proposed enlargement of its facilities. Suppose 250 business students were randomly sampled and 85 have personal computers at home. Conduct a test to see if the scale back of the proposed enlargement of its facilities is needed. Use ? = 0. 05. (Ans. H0 : p = . 3; Ha : p 0. 3; Large sample z-test for proportion; test score: Z = 1. 38; Rejection region; Z 1. 645; Do not reject H0 at ? = 0. 05. Scale back of the proposed enlargement of its facilities is not needed) 2 Example. A method currently used by doctors to screen women for possible breast cancer fails to detect cancer in 15% of the women who actually have the disease. A new method has been developed that researchers hope will be able to detect cancer more accurately. A random sample of 70 women known to have breast cancer were screened using the new method. Of these, the new method failed to detect cancer in six. Specify the null and alternative hypothesis that the researchers wish to test. Calculate the test statistic, determine the rejection region if ? = 0. 05, ? nd the p-value, and state the conclusion clearly in the language of this exercise. (Ans. H0 : p = 0. 15; Ha : p 0. 15; Test score: Z = ? 1. 51; Rejection Region: Z ? 1. 645; Do not reject H0 ; Insu? cient evidence to conclude that the new method is more accurate than the one currently used. -value= p(Z ? 1. 51) = 0. 5 ? 0. 4345 = 0. 0655) Example. The Midwest Organization of Retired Oncologists and Neurologists (M. O. R. O. N. ) has recently taken ? ack from some of its members regarding the poor choice of the organization’s name. The association bylaws require that more than 60% of the organization must approve a name change. Rather than convene a meeting, it is ? rst desir ed to use a sample to determine if a meeting is necessary. A random sample of 60 of M. O. R. O. N. ’s members were asked if they want M. O. R. O. N. to change its name. Forty-? ve of the respondent’s said †yes. Find the p-value for the desired test of hypothesis. (Ans. p-value= p(Z 2. 37) = 0. 0089) Example. Increasing numbers of businesses are o? ering child-care bene? ts for their workers. However, one union claims that more than 80% of ? rms in the manufacturing sector still do not o? er any child-care bene? ts to their workers. A random sample of 480 manufacturing ? rms is selected, and only 27 of them o? er child-care bene? ts. Specify the rejection region that the union will use when testing at alpha = . 05. (Ans. Ha : p 0. 8; Rejection region: Z 1. 645) 3 How to cite Statistics – Elements of a Test Hypothesis, Essay examples

Managing interdisciplinary Projects Change - MyAssignmenthelp.com

Question: Discuss about the Managing interdisciplinary Projects Change. Answer: Introduction Michelle and I founded the Breathe Again project and it involves giving care packages to less fortunate society members who are homeless. My supervisor and the project manager at Community Waitakere have already approved the project. The next step is to look for families that we will support and businesses that will be willing to sponsor the project. We will be linked to the homeless families through Vision West and The Ministry of Housing clinical leader. A power-point presentation has to be made to them concerning the project before they can assist us to get families (Banks et al, 2013). Once all these things are done, we can come up with the appropriate packages and the project can kick-off. We were able to do more sponsorship letters and used them to approach more businesses around the area. We also took advantage of some events, which were happening, in the Waitakere area to publicize our project and give out letters. There was a business forum in one of the conference center and we were able to give a small speech to the businessmen and women who attended. There was also a community event where we also spoke concerning our project. Many were impressed and promised to call or get back through our email (Wates, 2014). Some of the schools around the area were also interested in giving back to the community hence we also took sponsorship letters to them. We got email replies from five organizations. We finalized with the power-point presentation and showed it to the supervisor. We made it short, precise and catchy so that it would enhance our presentations (Vanclay et al, 2015). The presentation gave a summarized overview of our project and helped people see our vision in terms of what we were really aiming to achieve. It also enabled Michelle and I carry out separate presentations whenever we were given two similar appointments by different customers. This made us reach out to a number of business people. The meetings with Vision West and Ministry of housing happened in early November. We were able to make our presentation to them and they felt that we had a very good project. The said that the number of homeless people in New Zealand was on the rise hence they would appreciate any innovative projects that would help to take care of the homeless people. They institutions said they would help us get families that needed assistance but suggested that we first follow up on sponsorship (Vision West, 2017). They also said that we should come up with a write up of the specific packages that we would offer so that we discuss with them and see if they could be enhanced in any way. A subsequent meeting has been set up and will happen in two weeks. In this meeting, the organizations will come with the list of identified homeless families and my group will update on sponsorship. We will also discuss the specific packages and what they entail. Five of the local businesses responded and meetings were set up to do a presentation so that we could get sponsorship for the project. Michelle and I decided that we set the meetings over two weeks so that we would do thorough presentations that would enable us get sponsorship. We also decided to come up with specific budgets for the specific care packages before making the presentations to the businesses so that the sponsorship amounts were definite. The second meeting with Vision West and the Ministry of Housing went well. They came with a list of families who were homeless and really needed assistance. We were also able to come up with the specific care packages, which included provision of meals and homes, organizing meetings for families with similar circumstances and counseling and support packages. The organisations said they would give full support during the project to ensure that the families were well catered for and that everything progressed well (Vision West, 2017). We also updated them on the businessmen that had contacted us and that there was hope for sponsorship hence the project would kick off smoothly. We managed to have a meeting with three local businesses and made successful presentations about the breathe gain project. One of the businesses said they were a young business that had not really grown but they were willing to sponsor the team building activities that would bring together the homeless families. They said we should come up with a solid annual plan on how often these activities will take place and the place and budget and then we would discuss further on how they will be releasing funds (Top Ink, 2017). One of the businesses has accepted to sponsor the project by temporarily paying for homes that will be used to house the homeless. They will do this for a certain period while at the same time sponsoring start-ups of small businesses for the homeless so that they become self-reliant (Hertz Electrical, 2017). They were interested in knowing the history of the families that needed support, as they were willing to support five families for a start. Michelle and I were therefore to look at the suggested homeless families and come up with the neediest. The company would be willing to sponsor more families as time went by and if they managed to get the initial families to be self-sufficient. The third business requested that we give them some time and that they would get back to us (Honey Centre, 2017). We however still had meetings with two other companies set for late November. We updated Community Waikatere on the various developments that had taken place. They assured us of their full support in carrying out the project (Community Waikatere, 2017). Conclusion Overall, the project was a success as we were able to get two companies on board for the sponsorship. The homeless families would therefore receive the help that they needed and we will be able to learn more as the process continues (Van Rensburg, Meyer Nel, 2016). This project will assist homeless people in the area and will make them self-sufficient. It will also bring them together through team building activities hence help them have a positive view towards life. Recommendation Working together with Michelle was great and we decided to split tasks to enable us achieve more. It was a relief that the organizations finally responded to us and we were able to proceed with the project. We had a challenge in doing budgets but we got assistance and in the process learnt a lot about budgeting. This enabled us to come up with the required packages and present them in a professional manner to the various organizations that had requested for them (Brunswicker et al, 2016). As we progress with the project we will ensure that we have a solid plan that will enable us manage our time effectively and ensure that the project is a success. References Banks, S., Butcher, H. L., Orton, A., Robertson, J. (Eds.). (2013).Managing community practice: Principles, policies and programmes. Bristol,Policy Press. Brunswicker, S., Bagherzadeh, M., Lamb, A., Narsalay, R., Jing, Y. (2016). Managing Open Innovation Projects with Impact. Community Waitakere. (2017). Home. Retrieved from https://www.communitywaitakere.org.nz/ Hertz Electrical (2017). About. Retrieved from https://www.neighbourly.co.nz/business/hertz-electrical-ltd-1 Honey Center (2017). About Honey Centre Warkworth. Retrieved from https://www.neighbourly.co.nz/business/honey-centre-warkworth-ltd Top Ink (2017). About. Retrieved from https://www.neighbourly.co.nz/business/topink-ltd-printer-cartridge-expert van Rensburg, N. J., Meyer, J., Nel, H. (2016, December). Social innovation, research and community engagement: Managing interdisciplinary projects for societal change. InIndustrial Engineering and Engineering Management (IEEM), 2016 IEEE International Conference on(pp. 1785-1789). IEEE. Vanclay, F., Esteves, A. M., Aucamp, I., Franks, D. M. (2015). Social Impact Assessment: Guidance for assessing and managing the social impacts of projects. VisionWest. (2017). Community Trust. Retrieved from https://www.visionwest.org.nz/ Wates, N. (2014).The Community Planning Handbook: How people can shape their cities, towns villages in any part of the world. NY,Routledge.