(Points : 1) Answer: An investment that can change quickly without warning 5. Which of the following would not be part of an investment portfolio? (Select the best answer.) (Points : 1) Answer: A savings 529 plan 6. When is your risk tolerance lowest?
As shown in the fit put charts the S&P500 and GXP returns can be proven to be positively correlated by looking at the line of best fit with the data shown. The standard error is low as well being at 2.92%. The intercept or alpha in this regression is .0001809 which is not significantly different from zero. The t value is 15.56 which is greater than the t stat for a 5% significance level and the p value is less than .0001 which is the
The p-value is 0.002 which is smaller than the significance level. Hence there are 0.002 chances that such a small value can observe when the null hypothesis is true. Since, this probability is smaller than the significance level we reject the null hypothesis at 5% level. Hence, we conclude that there is enough evidence to support the manager’s claim that the average annual income was less than $50,000. b.
Interpret. From the scatter plot it is evident that the slope of the ‘best fit’ line is positive, which indicates that Credit Balance varies directly with Size. As Size increases, Credit Balance increases and vice versa. MINITAB OUTPUT: Regression Analysis: Credit Balance ($) versus Size The regression equation is Credit Balance ($) = 2582 + 404 Size Predictor Coef SE Coef T P Constant 2581.9 195.3 13.22 0.000 Size 404.13 51.00 7.92 0.000 S = 620.793 R-Sq = 56.7% R-Sq (adj) = 55.8% Analysis of Variance Source DF SS MS F P Regression 1 24200717 24200717 62.80 0.000 Residual Error 48 18498431 385384 Total 49 42699149 Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 4602.6 119.2 (4363.0, 4842.2) (3331.6, 5873.6) Values of Predictors for New Observations New Obs Size 1 5.00 2. Determine the equation of the ‘best fit’ line, which describes the relationship between CREDIT BALANCE and SIZE.
This provides us data saying that more of AJ DAVIS’s customers have a lower income then the rest. This difference is not to drastically different to effect the data too much. 3. Size (Household) Descriptive Statistics: Size Variable N N* Mean SE Mean StDev Minimum Q1 Median Q3 Maximum Size 50 0 3.420
Explain your rationale. Answer: Based on calculations above, I would recommend borrowing from National First Bank. This is because prime rate 3.25%, and 6.75% EAR of national first bank is only 10.25% Vs Regions best is higher 13.99%(14%). National First Bank is semiannually and although it has a prime rate low, the APR is low as well compared to Regions Best. 3.
This means that when Hamstring strength index 60 degree/s increases and Shuttle run test decreases. 4. Without using numbers, describe the relationship between the Hamstring strength index 120/s and the Triple hop index The relationship between the Hamstring strength index 120/s and the Triple hop index is r = 0.420. This is a moderate positive relationship since the r value falls between 0.3 to 0.5. This relationship is also statistically significant since the p value is less than the alpha value (0.019 and
d) minimize operational costs and maximize firm efficiency. e) maintain steady growth in both sales and net earnings. 4. Accounting concepts for a firm to create value it must: a) have a greater cash inflow from its stockholders than its outflow to them. b) create more cash flow than it uses.
A slow-down in economic growth C. A seasonal reduction in sales revenues D. Inadequate investment opportunities 5) Which of the following does NOT involve underwriting by an investment banker? A. Syndicated purchases B. Negotiated purchases C. Commission basis purchases D. Competitive bid purchases 6) __________ is a method of offering securities to a limited number of investors. A.
Table 3 (page 14), Descriptive Statistics, shows there is no discrepancies on the low or high side, which means that our statistics should be more true based on our findings. Table 4 (page 17), Confidence Interval Tables, shows that even though there is a variance between states in the incomes, the vast majority fall into a small variance, a few thousand dollars on either side. Table 5 (page 18), Hypothesis Testing, suggests the states have a smaller commute time than the mean of all of the states. Table 6 (page 19), a Regression Model, shows that the two charts show an 18% significance between the two. It therefore proves that commute time is not effected, as we believed, by commute time.