PART A :OK so here is the table for the health inspector; all you are really doing is 7+7+7, and so on:
PART A: health inspector: 7,14,21,28,35,42,49,56,63,70,77,84..........
PART A:same thing for the fire inspector, except this time your adding 12+12+12, and so on:
PART A: fire inspector: 12,24,36,48,60,72,84,96.......
PART B: and to figure out what day they will both come is you have to find the LCM (least common multiple)
PART B: which in this case is Day 84
hopes this helps!!!!!
6* 25 = 150 = (6*20= 120) + (6*5=30) Then Add 120+30= 150 so your answer is 5
Answer:
It will take her 10.5 hours to read the book
Step-by-step explanation:
She averages 16 pages every 30 minutes. If you take 336 and divide it by 16, you get 21 hours. But since she is reading 16 pages every half hour, that wouldn be correct. If it is asking how many hours it will take her to read the book, you have to take 16 and multiply it by 2. Then you get 32. Then, do the equation again. 336 divided by 32 is 10.5. So, if she reads the entire book in one go, it will take her 10 and a half hours to read the entire book, or 10.5.
There appears to be a positive correlation between the number of hour spent studydng and the score on the test.
When identifying the independent and dependent quantities, we think about what would cause the other to change. The score on the test would not cause the number of hours spent studying to change; rather, the number of hours spent studying would cause the score to change. This means that the number of hours studying would be the independent quantity and the score would be the dependent quantity.
Plotting the graph with the time studying on the x-axis (independent) and the score on the y-axis (dependent) gives you the graph shown. You can see in the image that there seems to be a positive correlation; the data seem to generally be heading upward.
Answer:
Reliability
Step-by-step explanation:
Here, we want to select the option that best completes the given question
The correct answer is the reliability
When we speak of how reliable a type of measurement is, we are simply referring to how free the particular measurement is from random error
Measurements that are free from random error are said to be reliable