Yes. try graphing it so that on the vertical axis you have "hours worked", and on the horizontal axis you have "pay". If the line slopes up as it goes right, then there is a positive correlation (ie, the more hours you work, the more money you get).
Yes, this is an example of a positive correlation. As the number of hours worked increases, the amount of money earned on the paycheck also increases. This relationship demonstrates a direct proportionality between the two variables.
Yes, research shows that there is a positive correlation between the number of hours spent in school and exam results in the UK. More time in school allows for more learning opportunities and revision, which can lead to improved academic performance in exams. However, the quality of teaching and student engagement are also important factors that can impact exam results.
The study may suggest a correlation between more hours of sleep and increased happiness, but it does not necessarily prove causation. Other factors could also contribute to a person's happiness, so it's important to consider the study's limitations and the potential influence of variables beyond just hours of sleep.
The study may suggest a correlation between more hours of sleep and happiness, but it does not definitively prove that one causes the other. Other factors or variables could be influencing the relationship between sleep and happiness. Additional research and studies are needed to establish a stronger causal relationship.
The present tense for "sleep" is "sleep." For example, "I sleep for eight hours every night."
5 days and 9 hours. or 129 hours or 7,740 minutes or 464,400 seconds.
POSITIVE CORRELATION IS CORRELATION THAT IS LINKED. REPHRAISED IT MEANS:POSITIVE CORRELATION IS CORRELATION IN WHICH BOTH AXIS ARE LINKED. SO IN SOME EXTREME CASES IT WOULD BE, (X=Y).BUT ON WITH THE QUESTION ANSWERING.HERE ARE A FEW EXAMPLES OF POSITIVE CORRELATION:1. THE AMOUNT OF COFFEE DRUNK AND THE NUMBER OF HOURS STAYED AWAKE.2. THE NUMBER OF PEOPLE FLYING TO AUSTRALIA AND THE NUMBER OF PLANES FLYING TO AUSTRALIA.THESE CAN EASILY BE CHANGED INTO SCATTER DIAGRAMS. IF YOU WANT TO KNOW MORE ABOUT POSITIVE CORRELATION THAN COME TO HAWLEY PLACE SCHOOL nd ask to see mr freeman.OTHER EXAMPLES OF POSITIVE CORRELATION IS THAT1.MARKS OF STUDENT AND HIS QUOTIENT. IN THIS CASE THERE IS POSITIVE CORRELATION BETWEEN THESE TWO VARIABLE.ON OTHER HAND IN SOME OTHER SITUATION "INCREASE IN VALUE OF ONE VARIABLE IS ASSOCIATED WITH INCREASE IN VALUE OF ANOTHER VARIABLE OR DECREASE IN VALUE OF ONE VARIABLE IS ASSOCIATED WITH DECREASE IN VALUE OF ANOTHER VARIABLE IS CALLED POSITIVE CORRELATION".
Correlation determines relationship between two variables. For example changes in one variable influence another variable, we can say that there is a correlation between the two variables. For example, we can say that there exists a correlation between the number of hours spent on reading and preparation and the scores obtained in the examination. One can infer that higher the amount of time spent on preparation may result in better performance in examination leading to higher scores. Hence the above is a case of positive correlation. If an increase in independent variable leads to an increase in dependent variable, it is a case of positive correlation. On the other hand if an increase in independent variable leads to a reduction in dependent variable, it is a case of negative correlation. An example for negative correlation could be the relationship between the age advancement and resistance to diseases. As age advances, resistance to disease reduces.
positive.
You might be referring to a positive correlation between grades and number of study hours.
The duration of Paycheck - film - is 1.98 hours.
Data can be correlated (meaning there is an indication of a relationship) either positively or negatively. The datasets of two variables (x,y) which have a negative correlations, when plotted, will show a negative trend, that means with increasing values of x, there will be, generally, decreasing values of y. An example of negative correlation, would be the more hours someone exercises, the less they weigh, if weight loss is measured as a negative number and weight gain as a positive number. In this case x= hours exercised, y = final weight - original weight. For presentation purposes, we frequently define our variable to show positive correlations. As per the above example, I could have defined y = original weight - final weight, which would show a positive correlation and plot as an upward trend. It would not change the absolute value of correlation just the sign. You may check wikipedia under correlation to get more understanding.
There has been no positive correlation with dreams and foods. Some say they do not sleep as well if they eat a heavy meal/food within three hours of sleeping.
A strong positive correlation does not prove causation. People only get sunburned during daylight hours. Sundials only work during daylight hours. Therefore sundials cause sunburns. The above sentences show how absurd such predicate thinking could be. Simply because two events usually occur at the same time does not mean they are related. One man found a perfect correlation between the price of whiskey and Chicago school teachers' salaries. No possible relationship could possibly exist except the rate of prosperity and inflation. Causation is difficult to prove.
1,480
It is your paycheck before any deductions, taxes or benefits are taken out. Simply how many hours you work multiplied by your hourly rate.
That should read "can employer CHANGE hours worked on timesheet and paycheck? My husband's employer goes in the computer system and changes my husband's hours to reflect 40 hours worked though he has worked many more hours than 40 each week. His paycheck also reflects that he just worked 40 hours. If your husband is on salary, then he is paid only for 40 hours. If he is hourly, then he should be paid for the hours he works. Of course, if overtime is against policy, then your husband should leave work after 40 hours.
Yes.