Tara runs an amusement park ride and needs to count the people who get on the ride. At the beginning of her shift, 132 people ha
d ridden the ride. The table shows the total number of riders for several times during Tara's shift.
Hours into Tara's shift
0 1 2 3
Total number of riders
132 165 198 231
What is the equation in slope-intercept form that represents the total number of riders over time?
Choose the correct expressions from the drop-down menus to create the equation in slope-intercept form.
Hours into Tara's shift
0 1 2 3
Total number of riders
132 165 198 231
What is the equation in slope-intercept form that represents the total number of riders over time?
Choose the correct expressions from the drop-down menus to create the equation in slope-intercept form.
2 answers:
Hi. You could easily find the slope-intercept form equation if you plot the points and do data fitting. You can use this with a software like MS Excel. The figure is attached in the image. Hence, the equation is y = 33x + 132, where y is the number of riders and x is the number of hours of Tara's shift.
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Answer:
Yes, this provide enough evidence to show a difference in the proportion of households that own a desktop.
Step-by-step explanation:
We are given that National data indicates that 35% of households own a desktop computer.
In a random sample of 570 households, 40% owned a desktop computer.
<em><u>Let p = population proportion of households who own a desktop computer</u></em>
SO, Null Hypothesis, : p = 25% {means that 35% of households own a desktop computer}
Alternate Hypothesis, : p
25% {means that % of households who own a desktop computer is different from 35%}
The test statistics that will be used here is <u>One-sample z proportion</u> <u>statistics</u>;
T.S. = ~ N(0,1)
where, = sample proportion of 570 households who owned a desktop computer = 40%
n = sample of households = 570
So, <u><em>test statistics</em></u> =
= 2.437
<em>Since, in the question we are not given with the level of significance at which to test out hypothesis so we assume it to be 5%. Now at 5% significance level, the z table gives critical values of -1.96 and 1.96 for two-tailed test. Since our test statistics doesn't lies within the range of critical values of z so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which we reject our null hypothesis.</em>
Therefore, we conclude that % of households who own a desktop computer is different from 35%.