Answer:
c. modus ponens
Explanation:
In propositional logic, we learn that <em>modus ponens</em> is a valid argument and a rule of inference. <em>Modus ponens</em> states that "P implies Q, and if P is true, then Q must be true."
Based on these propositions, we learn that all food that is healthy does not taste good, and tofu is healthy. Therefore,
<em>If all food that is healthy does not taste good,</em>
<em>and tofu is healthy to eat,</em>
<em>then tofu does not taste good.</em>
Answer:
The correct option is;
We cannot infer a cause and effect relationship because the multiple variables were included
Step-by-step explanation:
The criteria required in order to establish a cause and effect relationship includes the following;
1) There must be a temporal precedence between the cause and the effect such that the cause must take place before the effect
In the question, it is not clearly stated weather there was a divorce (the likely cause) takes place before the event
2) In the vent that the cause occurs, the effect must occur
Therefore, all those who are not married are expected to be deceased for there to be a cause and effect relationship
3) The cause and effect relationship must not be explicable by other factors
In the question, it is stated that those who were married were more likely to be active physically, maintain an healthy weight and were nonsmokers, which are factors that contribute to longevity.
Answer:
There is no convincing evidence at α = 0.10 level that the average vertical jump of students at this school differs from 15 inches.
Step-by-step explanation:
We have to make a hypothesis test to prove the claim that the average vertical jump of students differs from 15 inches.
The null and alternative hypothesis are:
The significance level is 0.10.
The sample mean is 17 and the sample standard deviation is 5.37.
The degrees of freedom are df=(20-1)=19.
The t-statistic is:
The two-sided P-value for t=1.67 is P=0.11132.
This P-value is bigger than the significance level, so the effect is not significant. The null hypothesis can not be rejected.
There is no convincing evidence at α = 0.10 level that the average vertical jump of students at this school differs from 15 inches.
Answer:
Example of qualitative variable: hair colour.
Example of discrete quantitative variable: age.
a) Qualitative data displays are pie charts, histograms
b) Quantitative data displays are scatter and line graphs.
Step-by-step explanation:
A qualitative variable expresses a non-numerical quality of an object or person. For example, hair colour (brown, blonde, red...) or eye colour (green, blue, brown...).
A quantitative variable is a numerical value. For example, temperature (100 K, 2000 K...) or age (12 years, 20 years...).
A discrete quantitative variable can be obtained by counting, like the number of cars in a road. This is plotted in scatter graphs. For continuous variable, it can be obtained by measuring, like the height of your family members. This is plotted in line graphs.
- Pie charts: is a circular graphic that shows the statistics or number of people or objects with certain characteristics. For example, how many people have brown hair, how many are blonde and how many are redheaded.
- Histograms: they show vertical bars associated with the qualitative variable in the x-axis and the number of objects or people with that characteristic in the y-axis.
- Scatter: it is a graph with x and y axis and using Cartesian coordinates. Since it is for quatities, numbers can be represented as points.
- Line graphs: it is basically the same as a scatter plot but in this case the points can be joined by a line because the quantities are connected or are continuous.
1) the form of the equation may be written as y = A(X - Xo)(X - X1)
Where Xo and X1 are the two roots of the equation.
2) We can fix the system of coordinates so that the vertex is in the middle of the gate => Xo = - 40 and X1 = +40
=> y = A (X + 40) (X - 40) = A (X^2 - 1600)
3) The height, at X = 0 is 25
=> A(0 - 1600) = 25
=> -1600A = 25 => A = -25 / 1600 = - 1/64
4) The equation is y = - [1/64] (X^2 - 1600)
5) You can present it in different equivalent forms.
Some of those other forms are:
1) - 64y = (x^2 - 1600)
2) x^2 = - 64y + 1600
3) X^2 = - 64 (y - 25)
