<h2>
Explanation:</h2>
Remember you need to write complete questions in order to find exact answers. In this way you haven't provided any function, so I'll choose a quadratic function given by:
So we need to find the entire interval at which this function positive. Put another way:
By using graphing tool, we get the graph shown below. As you can see:
- The function decreases from
- The function increases from
- The graph of the function is a parabola that opens up.
But what is really importan in this problem is that:
- The function is positive over the interval
At this interval the function is positive, that is,
<h2>Learn more:</h2>
Standard equation of the graph of a parabola:
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5/6F - 3/4F = 1/4
5x4/24F - 3x6/4F = 1/4
20/24F - 18/24F = 1/4
20F - 18F = 1/4x24
2F = 6
F = 6/2
F = 3
Answer:
Step-by-step explanation:
Hi there!
Linear equations are typically organized in slope-intercept form: 
where <em>m</em> is the slope and <em>b</em> is the y-intercept (the value of y when the line crosses the y-axis)
Given that the slope is 3, we can plug this into y=mx+b as <em>m</em>:
Now, to solve for <em>b</em>, simply plug in the given point:
Therefore, the y-intercept is 5. Plug this back into the equation:
I hope this helps!
Answer:
<em>The total percentage discount was 19%</em>
Step-by-step explanation:
<u>Percentages</u>
Suppose the original price of the shirt was x.
A discount of 10% reduces the price by:
10*x/100 = 0.1x
Thus, the discounted price is:
x - 0.1x = 0.9x
The second discount reduces the price by:
10*0.9x/100 = 0.09x
The new discounted price is:
0.9x - 0.09x = 0.81x
With respect to the original price, the last discounted price has been discounted by:
x - 0.81x = 0.19x
This means the total percentage discount was 0.19*100 = 19%.
The total percentage discount was 19%
If the p-value is smaller than the level of significance, then it indicates strong evidence against the null hypothesis, as there is less than a 5% probability the null hypothesis is correct.
In this question,
A p-value is a probability, calculated after running a statistical test on data and it lies between 0 and 1. The p-value only tells you how likely the data you have observed is occurred under the null hypothesis.
One of the most commonly used p-value is 0.05. If the value is greater than 0.05, the null hypothesis is considered to be true. If the calculated p-value turns out to be less than 0.05, the null hypothesis is considered to be false, or nullified (hence the name null hypothesis).
A small p-value (< 0.05 in general) means that the observed results are unusual, assuming that they were due to chance only. Now, the smaller the p-value, the stronger the evidence that should reject the null hypothesis.
Hence we can conclude that if the p-value is smaller than the level of significance, then it indicates strong evidence against the null hypothesis, as there is less than a 5% probability the null hypothesis is correct.
Learn more about p-value here
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