Step-by-step explanation:
-1/ 4 , -2/4 , 0.20 , 0.90 ,3/4 ,1.50 - 0.50 ,7/4
because if you changed them whole to decimal it shows the result
-1/4 = - 0.25
-2 / 4 = - 0.5
3 / 4 = 0.75
1.50 - 0.50 = 1
7/4= 1.75
0.20 and 0.90 are already decimal numbers
Answer:
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Step-by-step explanation:
The zqy I got to this is; é+& = ":
Answer:C
Step-by-step explanation:
In order to make the offer attractive such that it would earn £25,000 for Ian Vector, Paddington Games would have to sell 460 games.
The game can be sold for £25,000 or for £2,000 and then a fee of £50 for every game sold.
In order for the amount to be the same, the amount from games sold will have to equal the difference between the £25,000 and the £2,000.
Difference is:
= 25,000 - 2,000
= £23,000
The <u>number of games to be sold</u> is:
= Difference / Amount per game
= 23,000 / 50
= 460 games
In conclusion, 460 games need to be sold to make the offer attractive.
<em>Find out more at brainly.com/question/2865277.</em>
Answer:
Step-by-step explanation:
You need to assume that the slope between the dependent Varian and the numerical independent variable is zero.
In regression analysis, to find the effect of one independent variable on the dependent variable, there has to be no interference from the other independent variables whether they be categorical (dummy) or numerical independent variables.
A dummy variable is one which takes on the value of 0 or 1, to represent the absence or presence (respectively) of a given category which is expected to influence the dependent variable.
When a dummy independent variable is included in a regression model, to know the effect of that dummy or category (e.g. day =1, night =0) on the dependent variable, the influence of the numerical independent variable has to be removed temporarily.
In a regression equation,
Y=a+bX+cK
Y is the dependent variable
a is the intercept on the vertical axis on the graph
b is the slope between the dependent variable Y and the independent numerical variable X
c is the slope between the dependent variable Y and the dummy variable K
