It is difficult to do this interpretation because there may not have been time for the outcome to have developed. For example, in Venezuela right now there is an attempt by part of the opposition to defeat the government through street violence and reverse the social gains of Hugo Chavez and Nicolas Maduro but the dispute still has not been resolved.
Answer:
The answer is D. $1,192,000 net cash inflow
Explanation:
For financing activities under cash flow, inflows are what is coming in like issuance of bond, obtaining loan from bank. This money is coming into the business for investments and outflows are what is going out of the business e.g paying dividend to shareholders.
The inflows here are:
The issuance of 20,000 shares of $1 par common stock for $40 per share which is $800,000(20,000 shares x $40 per share) and also the long-term notes payable of $440,000
Therefore total inflows are $800,000 + $440,000
=$1,240,000
There is only one outflow which is the dividends of $48,000
So what will be reported under cash flows from financing activities is
$1,240,000 - $48,000
= $1,192,000
Answer:
Explanation:
Each of these effects would most likely influence Tommy's order differently. The real-income effect would most likely cause Tommy to buy the large steak and salad regardless of the increase in price since individuals tend to spend more when they start making more money. The substitution effect on the other hand would most likely cause Tommy to order a smaller steak since it costs more but at the same time order, more salad since the price has not increased as the steak did.
Answer:
F. A linear model on Size accounts for 68.6% of the variation in home Price.
Explanation:
R-squared () is a statistical measure used in a regression model to describes the percentage or proportion of variance or variation in a dependent variable which is explained by or can be predicted from the independent variable of the model.
R-squared is also known the coefficient of determination.
In the question, the dependent variable is the price, while the independent variable is the size. That is why the aim is to determine the percentage or proportion of variance or variation of price of homes which is explained by or can be predicted from the size of homes.
Given the R-squared of 68%, the correct answer is option F which states that "a linear model on Size accounts for 68.6% of the variation in home Price". This implies that 68% variation in the price of home can be explained by or predicted from the size of home.
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