As seen from Graph 1 (Resistance vs. Current) there is not any particular significant relationship between resistance and current. According to Ohm’s Law, when resistance increases, current should have decrease or vice versa. There is no such display of that kind of relationship in Table 1 and Graph 1. The data does not make sense since in a circuit, the current and resistance should influence each other in some type of way. The data did not agree with the expectations.…
Also, the p-value obtained for Nobel is 0.514321, which is quite high and more that than 0.05 (Significance level assumed to be 95%). Hence, this variable (Nobel) is not significantly determining the no. of tickets sold. Model 2: Simple Linear Regression Model between TIX (No. of Tickets Sold) and O4 (Yankees as Opposition) Exhibit 3 shows the detail analysis of this regression model.…
However, Fama-French model is not so good. Firstly, the β of ExRm and HML is insignificant, that is to say, the expect return of mutual funds is little related to market premium and stocks value. So it is meaningless to put ExRm and HML into the model. Secondly, the R-square of Fama-French model is low, maybe because the model omits some variables that highly explain the risk premium of mutual funds.…
Significant findings were explained, however non-significant findings were not explained. This made the interpretation of the data difficult because it did not explain whether this might have been attributed to a small sample…
For example, using a standard deviation of a highly correlated distribution of stocks that includes 3 kitchen & bath companies and 3 engine & generator companies, the Beta will decrease from 2.67 to 1.52. Then, the new WACC would be 10.40%[Table 5]. Just this difference in Beta would make the per share value of the stock go from $164K to $251K with 0 discount (due to the lack of control and liquidity), and from $ 57K to $ 88K with 65 % discount [Table 7]. Kohler is most likely using a relatively high WACC and high discount to come up with a $58K value per share. As it is shown in Table 8, using a WACC of 14.19% and a discount of 65% for liquidity and control of the stock arrives at $57K per share.…
In week 1, the T-value (df=95) is 1.848. This generates a p-value of 0.068, which exceeds Fisher’s threshold and therefore null-hypothesis is hold. There is no significant difference in sales performance when compare males (mean=4232.34) to females (mean=5227.86). In week 2, the T-value (df=95) is 2.828 and the p-value derived is 0.006. Here, the possibility that the difference is due to mere random chance is less than 1% therefore the difference in sales performance between males (mean=4175.92) and females (mean=5675.97) in week 2 is strongly significant.…
In July 2008, during half year it lost almost 70% of its value by reaching its maximum ( 147.26$ per barrel). As a main reason of that “boom”, excessively heat with speculative capital was shown by analytics. Although, principally 100$ for a barrel is acceptable, but its price ,definitely, can not be 140$. As a result, oil price was stabilized around 40-50$/barrel, but dropped till 38-42$/barrel in spring 2009. At that time, it get rid of dependency of dynamic of USA currency.…
In Nolan E. Hertel’s article, he found that for every kilowatt per hour of energy that nuclear power produces it costs around 1.7 cents. In comparison, it takes 2.4 cents for coal, 6.7 cents for natural gas and 10.2 cents for oil to produce the same amount of money (2008). Nuclear energy has a remarkably low price in the cost. Clearly from the research reviewed, the cost of nuclear power is far less overall than other sources of…
When all five groups were included, the variation in germination rates was significant (χ2=35.25, df=4, pp>0.10). When the 4,000,000 rads dose is included, the survival rate decreases from being above 61% to 0%, and this difference is significant (χ2=22.71, df=4, p<0.0001). The differences between the 50,000 rads and 150,000 rads as well as the 50,000 rads and 500,000 rads were found to be not…
The Forecasting for the June 15th financial instruments of the S&P 500, 10 year T-Notes (yield), the gold price, the oil (WTI), the unemployment rate, and the Euro. My reasoning for these instruments was a mix between guessing and little economic reasoning. Out of the 6 financial instruments I was closest to 10 year T-Notes (yield), and the oil (WTI). While the other four instruments I was either in the right direction or the market went in the opposite of what I predicted. On May 18th the S&P 500 was at 2129.3 my forecast for June 15th was 2178.…