A null hypothesis is the hypothesis that there is no significant difference between specific populations, where observed differences are due to errors. The Hardy-Weinberg Theory is a null hypothesis and that is what we tested in this experiment. The only time a null hypothesis can be accepted or rejected but cannot be proven. It may be quantified as true, but it cannot be proven. The reason for this is because in tests like these observed differences are usually due to chance differences in sampling.
This section would focus on the possible cons of adopting IFRS in the U.S. faced by the same group of people discussed above. The auditors will have to make changes to the reports from the previous years for the comparative purposes. The public companies would have to bear a heavy monetary cost of transition from the U.S. GAAP standards to IFRS. It may affect the prices of the stocks of these companies, which in turn would be faced by the investors. This can affect the growth of the company.
| The questions on a survey may be poorly constructed. | Correlational Research | Clarifies the relationship between variables that cannot be examined by other research methods. | This method does not permit conclusion regarding cause and effect. | Experimental Research | Allows to opportunity to draw case and effect relationships. | The type of setting may influence the subjects’ behavior.Researcher could be bias.
WACC is the minimum return required by the investors * As I said in the last bullet there are many different to interpret the numbers in WACC and the way Cohen did it is one way but there is different ways to interpret the data given. One of the things I see that I would do different is how she calculated the weight of the equity. I would do it by multiplying the number of shares outstanding by the price of the stock. I also found the cost of debt a little differently by using the present and future values to find i for the cost of debt. 2.
Science tends to prefer the simplest explanation that is consistent with the data available at a given time. Karl Popper preferred the simplest explanation because the content is usually greater, and they are better testable. A guy by the name of Elliot Scott argued popper’s theory on Occam’s razor. Elliot said “The simplest theory is the more likely to fail. In science you need an explanation behind everything you do.
• Different investors have different views about which screening metrics an investor should use to reduce the number of mutual funds down to a more manageable set for evaluation in detail. Even the criticism about the rating, it offered value to investors for reference. For example, an evaluation system, which takes in to account the future perspective, can’t promise the return and its forecast precision, just like the analyst report. Hence, there are still some investors see Morningstar ratings as one of the resource to find winning mutual funds (2) Based on the case, we noticed that Morningstar ratings are indicators of past performance, and should not be used
It was used originally as leveraged buyout investors examined distressed companies that needed financial restructuring. They used EBITDA to calculate quickly whether these companies could pay back the interest on certain financed deals. It quickly evolved into a tool to determine whether a company could pay back its debt in the near term. Because EBITDA helps measure the company’s underlying profit, banks and other sources of capital tended to use EBITDA when determining how much money they could
As for stockholders they mainly use this information for forecasting dividends, earnings on the free cash flow. Question 2 What qualitative factors should analysts look for when evaluating a company’s likely future financial performance? Explain. When evaluating a company's future financial performance, some qualitative factors that should be considered are future prospects, the current environment weather it may be legal or regulatory, the competition , economy, the level of dependents on the
Unlike the mean, sample medians do not fall into a normal distribution, because medians do not use all of the available information in the sample. The main weakness of a nonparametric test is that it may have less power than the equivalent parametric test. 3). Why do you use the chi-square statistic? What type of data is used with chi-square analysis?
Most scoring models are not sufficiently precise to trust small differences in total scores. Furthermore, ranking projects by their project scores is generally incorrect anyway (Campbell, G. M. (2014)). Typical scoring systems ignore project cost and, therefore, fail to represent "bang for the buck." Prioritizing projects requires being able to estimate the costs, value, and risks of alternative project portfolios. But, both sides of the equation are difficult.