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When the sample size increase what will happen to the 95 percent confidence interval?
It becomes narrower.
What happens as the number of classes in a histogram increase?
The columns become narrower, their heights become more accurate but possibly more variable. The chart contains more of the underlying detailed information.
PLOT A VARIABLE WITH NORMAL DISTRIBUTION WITH MEAN 200 AND DEVIATION 20. SUPERIMPOSED WITH THE PREVIOUS FIGURE, PLOT THE DISTRIBUTION OF THE ARITHMETIC MEAN OF SAMPLES OF SIZE N=4, 25 AND 100, OF THAT POPULATION?
A normal distribution with a mean of 200 and a deviation of 20 can be plotted as a bell-shaped curve, as shown in the figure below. Superimposed on the figure, the distribution of the arithmetic mean of samples of size n=4, 25 and 100 can be plotted as shown in the figure below. The arithmetic mean distribution for n=4 is a much narrower distribution than a normal distribution, since it is based on a small sample size. As the sample size increases, the distribution becomes wider and more similar to the normal distribution.
Which is the best estimate of the length of a mattress?
In general, mattresses are about 75 inches long. King mattresses are about 80 inches. Cal King mattresses are narrower, but are usually 84 inches long.
What is the difference between field size and field range?
Field size refers to the total number of possible values that a field can take, often determined by the data type (e.g., a 32-bit integer can represent values from -2,147,483,648 to 2,147,483,647). Field range, on the other hand, denotes the specific subset of values that are valid or acceptable for a particular field within a given context, which may be narrower than the full field size. For example, while the field size for a date field might allow any date value, the field range could limit it to a specific year or date format.
True or False The higher the confidence level the narrower the confidence interval?
True.
What are the two ways to shorten a confidence interval?
To shorten a confidence interval, you can either increase the sample size or reduce the confidence level. Increasing the sample size decreases the standard error, leading to a narrower interval. Alternatively, lowering the confidence level (e.g., from 95% to 90%) reduces the range of the interval but increases the risk of capturing the true population parameter.
When the sample size increase what will happen to the 95 percent confidence interval?
It becomes narrower.
In a poll of 100 adults 45 percent reported they believe in faith healing If the poll was based on 5000 adults would the confidence interval be wider or narrower?
The formula for margin of error is (Z*)*(Standard Deviation))/(sqrt(N)), so as N increases, the margin of error decreases. Here N went from 100 to 5000, so N has increased by 4900. This means the margin of error decreases. Since the confidence interval is the mean plus or minus the margin of error, a smaller margin of error means that the confidence interval is narrower.
What affect does increasing the sample size have on the width of the confidence interval?
Increasing the sample size decreases the width of the confidence interval. This occurs because a larger sample provides more information about the population, leading to a more accurate estimate of the parameter. As the sample size increases, the standard error decreases, which results in a narrower interval around the sample estimate. Consequently, the confidence interval becomes more precise.
What does confidence interval for the mean estimate?
A confidence interval for the mean estimates a range within which the true population mean is likely to fall, based on sample data. It provides a measure of uncertainty around the sample mean, indicating how precise the estimate is. The interval is constructed using a specified confidence level (e.g., 95%), which reflects the degree of certainty that the interval contains the true mean. A wider interval suggests more variability in the data, while a narrower interval indicates greater precision in the estimate.
What combination of factors would definitely reduce the width of a confidence interval?
To reduce the width of a confidence interval, one can increase the sample size, as larger samples tend to provide more precise estimates of the population parameter. Additionally, using a lower confidence level (e.g., 90% instead of 95%) decreases the interval's width. Finally, reducing the variability in the data, such as by controlling for extraneous factors or using a more homogenous sample, can also lead to a narrower confidence interval.
How can you decrease the width of a confidence interval without sacrificing the level of confidence?
To decrease the width of a confidence interval without sacrificing the level of confidence, you can increase the sample size. A larger sample provides more information about the population, which reduces the standard error and narrows the interval. Additionally, using a more precise measurement technique can also help achieve a narrower interval. However, it's important to note that increasing the sample size is the most effective method for maintaining the desired confidence level while reducing width.
What happen to the width of a confidence interval if the sample size is doubled from 100 to 200?
When the sample size is doubled from 100 to 200, the width of the confidence interval generally decreases. This occurs because a larger sample size reduces the standard error, which is the variability of the sample mean. As the standard error decreases, the margin of error for the confidence interval also decreases, resulting in a narrower interval. Thus, a larger sample size leads to more precise estimates of the population parameter.
What happens to the confidence interval when you increase the sample size?
When you increase the sample size, the confidence interval typically becomes narrower. This occurs because a larger sample size reduces the standard error, leading to more precise estimates of the population parameter. As a result, while the confidence level remains the same, the interval reflects increased certainty about the estimate. However, the actual confidence level (e.g., 95%) does not change; it simply provides a tighter range around the estimate.
When the larger values of the standard deviation result in a normal curve that narrower and more peak?
Smaller
Is it true that The smaller the standard deviation of a normal curve the higher and narrower the graph?
Yes, that's true. In a normal distribution, a smaller standard deviation indicates that the data points are closer to the mean, resulting in a taller and narrower curve. Conversely, a larger standard deviation leads to a wider and shorter curve, reflecting more variability in the data. Thus, the standard deviation directly affects the shape of the normal distribution graph.
