Confidence Intervalput Values In Green Cells Output Or Answers In Yel ✓ Solved

Confidence Interval Put values in GREEN cells; output or answers in YELLOW cells Enter input in blue cells ; Look for answers in yellow cells t or z Confidence Interval for µ Confidence Interval for p Proportions Confidence Level 0.990 Enter decimal Confidence Level 0.950 Enter decimal n 27 n 329 Mean 17.3185 Number of Successes 141 StDev 3.4029 pop stdev no Enter yes if population stdev known Enter No if population stdev is unknown SE 0.654888 Sample Proportion 0.428571 t 2.779 SE 0.027283 Margin of Error 1.819935 z 1.960 Lower Limit 15.498565 Margin of Error 0.053475 Upper Limit 19.138435 Lower Limit 0.375096 Upper Limit 0.482046 sample mean & standard deviatio Put values in blue cells; output or answers in YELLOW cells Enter values starting from B5 cell Data 18.4 Mean 17..1 Sample Standard Deviation 3.......................4 Minimum Sample Size Enter input in blue cells ; Look for answers in yellow cells Minimum Sample Size μ for population mean Minimum Sample Size p for Proportion Confidence Level 0.950 Enter decimal Confidence Level 0.920 Enter decimal StDev 10 Sample Proportion 0.5 If sample proportion unknown enter 0.5 Error 3 Error 0.03 Write percentage as decimal z-Value 1.960 z-Value 1.751 Minimum Sample Size 43 Minimum Sample Size 852 EMPIRICAL RULE Empirical Rule using standard error for CONFIDENCE INTERVAL ANSWER Empirical Rule .7 mean 0.43 Lower number Upper number standard deviation % 0.37 0.49 Standard error 0.% 0.31 0..70% 0.25 0.61 Deconstructing a Documentary Film As you view the film, use this worksheet to identify the director’s main points/arguments.

You must identify at least five (5) arguments. The remaining five (5) are optional. However, by identifying more points/arguments than you need in order to write a good essay, you give yourself the luxury of choosing which ones you would like to respond to. Director’s Thesis: Click here to enter text. Director’s Argument Agree or Disagree?

Why or Why Not? Point/Argument #1 Click here to enter text. Click here to enter text. Click here to enter text. Point/Argument #2 Click here to enter text.

Click here to enter text. Click here to enter text. Point/Argument #3 Click here to enter text. Click here to enter text. Click here to enter text.

Point/Argument #4 Click here to enter text. Click here to enter text. Click here to enter text. Point/Argument #5 Click here to enter text. Click here to enter text.

Click here to enter text. Point/Argument #6 Click here to enter text. Click here to enter text. Click here to enter text. Point/Argument #7 Click here to enter text.

Click here to enter text. Click here to enter text. Point/Argument #8 Click here to enter text. Click here to enter text. Click here to enter text.

Point/Argument #9 Click here to enter text. Click here to enter text. Click here to enter text. Point/Argument #10 Click here to enter text. Waiting for Superman Essay Instructions and Guidelines You probably have quite a bit of experience reading and summarizing.

Since grade school, you have been writing book reports and suffering through summer reading programs. Reading, comprehending, and summarizing are vital skills. At the college level, however, simply regurgitating material is insufficient. One of the most important benefits of a college education is the ability to think critically. Understanding someone else’s ideas and then responding to them is one of the most common tasks you will encounter in your college classes.

And although your future employer may never ask you to provide a literary analysis of The Scarlett Letter or a research paper about global warming, you will be expected to exercise critical thinking skills on a regular basis. Assignment: Write a summary-and-response essay about the documentary, Waiting for Superman. You are not being asked to discuss whether you like/dislike the film or agree/disagree with the ideas set forth in it. Instead, you are being asked to deconstruct the film and assess the validity of the arguments set forth in it. The summary portion of the essay should be fairly brief, preferably limited to the introductory paragraph but certainly no more than one body paragraph.

Your response should take up the bulk of the paper. Requirements: • For this essay, you will incorporate two secondary sources. You may use the “Waiting for Superman Rebuttal†articles as your sources, or you may choose your own sources after conducting research. You must properly incorporate these sources into the essay, using signal phrases to introduce the sources and using parenthetical citations to credit the authors. You also will include a Works Cited page with correct MLA citations for each source.

In addition, you must properly cite Waiting for Superman. • You must adhere to the formatting guidelines set forth in The MLA Handbook, 8th edition. Be sure that all margins measure 1 inch and that you use the Times New Roman 12-point font. You should also follow MLA formatting guidelines regarding the page heading, running header, page numbering, etc. Finally, your citations must conform to MLA citation style. • The essay’s assigned length is 1,000ï€1,200 words. Guidelines: Step 1.

Grab some snacks and watch the film. The first time you view the film, do not take notes. Just enjoy it (hopefully) like you would any other movie. Step 2. Watch the movie a second time.

This time, you should pay close attention to the director’s argument. In addition, you should try to identify the director’s purpose and intended audience. Take notes. Write down any relevant facts or statistics. Step 3.

Write a response to the film. Some questions to consider: • What did you think about the film? • Do you agree or disagree with the ideas set forth in it? • Does the director convincingly prove his thesis? If not, why? • What are the director’s underlying assumptions? • What is Guggenheim assuming that you will agree/disagree with? • Does Guggenheim omit information that would damage his argument? If so, what information does he omit? • What rhetorical strategy/strategies does Guggenheim use? (See for more information about rhetorical strategies). Step 4.

Complete the “Deconstructing a Documentary Film Worksheet.†Step 5. Write the summary portion of the essay. Do not write the film equivalent of a book report. Instead, identify the director’s thesis and then summarize the evidence he uses to support that thesis. Be objective.

Do not allow your own thoughts to creep into your summary. Step 6. For the response section of the essay, choose one of the following strategies for writing a response essay: • Analyze the effectiveness of the director’s argument – In this case, the response analyzes key features, such as the clarity of the main idea; the organization of the argument; the quality of the supporting evidence; and/or the effectiveness of the author's style, tone, and voice. • Agree or disagree with the director’s argument - Often, responders react to the ideas or the argument of the essay. In this case, the responders show why they agree or disagree with what the director says. • Interpret and reflect on the director’s argument - The responder examines the underlying assumptions or the implications of the director’s argument.

Often the responder reflects on how his or her own experiences, attitudes, and observations relate to the film. Confidence Interval Put values in GREEN cells; output or answers in YELLOW cells Enter input in blue cells ; Look for answers in yellow cells t or z Confidence Interval for µ Confidence Interval for p Proportions Confidence Level 0.990 Enter decimal Confidence Level 0.950 Enter decimal n 27 n 329 Mean 17.3185 Number of Successes 141 StDev 3.4029 pop stdev no Enter yes if population stdev known Enter No if population stdev is unknown SE 0.654888 Sample Proportion 0.428571 t 2.779 SE 0.027283 Margin of Error 1.819935 z 1.960 Lower Limit 15.498565 Margin of Error 0.053475 Upper Limit 19.138435 Lower Limit 0.375096 Upper Limit 0.482046 sample mean & standard deviatio Put values in blue cells; output or answers in YELLOW cells Enter values starting from B5 cell Data 18.4 Mean 17..1 Sample Standard Deviation 3.......................4 Minimum Sample Size Enter input in blue cells ; Look for answers in yellow cells Minimum Sample Size μ for population mean Minimum Sample Size p for Proportion Confidence Level 0.950 Enter decimal Confidence Level 0.920 Enter decimal StDev 10 Sample Proportion 0.5 If sample proportion unknown enter 0.5 Error 3 Error 0.03 Write percentage as decimal z-Value 1.960 z-Value 1.751 Minimum Sample Size 43 Minimum Sample Size 852 EMPIRICAL RULE Empirical Rule using standard error for CONFIDENCE INTERVAL ANSWER Empirical Rule .7 mean 0.43 Lower number Upper number standard deviation % 0.37 0.49 Standard error 0.% 0.31 0..70% 0.25 0.61 J LU TERMINOLOGY 101 Confidence intervals: Part 2 MAHER M.

EL-MASRI, RN, PhD, IS AN ASSOCIATE PROFESSOR AND RESEARCH LEADERSHIP CHAIR IN THE FACULTY OF NURSING, UNIVERSITY OF WINDSOR, IN WINDSOR, ONT. Confidence interval: The range of values, consistent with the data, that is believed to encompass the actual or "true" population value Source: Lang, T.A., & Secic, M. (2006). How to Report Statistics in Medicine. (2nd ed.). Philadelphia: American College of Physicians Part 1, which appeared in the February 2012 issue, introduced the concept of confidence intervals (CIs) for mean values. This article explains how to compare the CIs of two mean scores to draw a conclusion about whether or not they are statistically different.

Two mean scores are said to be statistically different if their respective CIs do not overlap. Overlap of the CIs suggests that the scores may represent the same "true" population value; in other words, the true difference in the mean scores may be equivalent NurseONE resources ON THIS TOPIC EBSCO-MEDLINE FULL-TEXT ARTICLES • Hildebrandt, M., Vervà¶lgyi, E., & Bender, R. (2009). Calculation of NNTs in RCTs with time-to-event outcomes: A literature review. BMC Medical Research Methodology, 9,21. • Hildebrandt, M., Bender, R., Gehrmann, U., & Blettner, M. (2006). Calculating confidence intervals for impact numbers. àŸ/MCMed/co/ Research Methodology, 6, 32. • Altman, D.

G. (1998). Confidence intervals forthe number needed to treat. BMJ (Clinical Research Ed.), ), . MYàŽLIBRARY • Campbell, M. |., Machin, D., & Walters, S. I. (2010).

Medical statistics: A textbook for the health sciences (4th ed). • Mateo, M. A., & Kirchhoff, K. T. (Eds.). (2009). Research for advanced practice nurses: From evidence to practice. • Webb, C, & Roe, B. (Eds.). (2007). Reviewing research evidence for nursing practice: Systematic reviews. to zero.

Some researchers choose to provide the CI for the difference of two mean scores instead of providing a separate CI for each of the mean scores. In that case, the difference in the mean scores is said to be statistically significant if its CI does not include zero (e.g., if the lower limit is 10 and the upper limit is 30). If the CI includes zero (e.g., if the lower limit is -10 and the upper limit is 30), we conclude that the observed difference is not statistically significant. To illustrate this point, let's say that we want to compare the mean blood pressure (BP) of exercising and sedentary patients. The mean BP is 120 mmHg (95% CI mmHg) for the exercising group and 140 mmHg (95% CI mmHg) for the non-exercising group.

We notice that the mean BP values of the two groups differ by 20 mmHg, and we want to determine whether this difference is statistically significant. Notice that the range of values between 120 and 130 mmHg falls within the CIs for both groups (i.e., the CIs overlap). Thus, we conclude that the 20 mmHg difference between the mean BP values is not statistically significant. Now, say that the mean BP is 120 mmHg (95% CI mmHg) for the exercising group and 140 mmHg (95% CI mmHg) for the sedentary group. In this case, the two CIs do not overlap: none of the values within the first CI fall within the range of values of the second CI.

Thus, we conclude that the mean BP difference of 20 mmHg is statistically significant. Remember, we can use either the CIs of two mean scores or the CI of their difference to draw conclusions about whether or not the observed difference between the scores is statistically significant. • 10 CANADL!\N-NURSE.COM However, users may print, download, or email articles for individual use. TH E R ES EA R c H F IL E Il lu S T r a T IO n : V A N N I L O R Ig g IO To draw conclusions about a study population, researchers use samples that they assume truly represent the population. The confidence interval (CI) is among the most reliable indicators of the soundness of their assumption. A CI is the range of values within which the population value being studied is believed to fall.

CIs are reported in the results section of published research and are often calculated either for mean or proportion data (calculation details are beyond the scope of this article). A 95% CI, which is the most common level used (others are 90% and 99%), means that if researchers were to sample numerous times from the same population and calculate a range of estimates for these samples, 95% of the intervals within the lower and upper limits of this range will include the population value. To illustrate the 95% CI of a mean value, say that a sample of patients with hypertension has a mean blood pressure of 120 mmHg and that the 95% CI for this mean was calculated to range from 110 to 130 mmHg. This might be reported as: mean 120 mmHg, 95% CI mmHg.

It indicates that if other samples from the same population of patients were generated and intervals for the mean blood pressure of these samples were estimated, 95% of the intervals between the lower limit of 110 mmHg and the upper limit of 130 mmHg would include the true mean blood pressure of the population. Notice that the width of the CI range is a very important indicator of how reliably the sample value represents the population in question. If the CI is narrow, as it is in our example of mmHg, then the upper and lower limits of the CI will be very close to the mean value of Confidence interval: The range of values, consistent with the data, that is believed to encompass the actual or “true†population value Source: Lang, T.A., & Secic, M. (2006).

How to Report Statistics in Medicine. (2nd ed.). Philadelphia: American College of Physicians the sample. This sample mean value is probably a more reliable estimate of the true mean value of the population than a sample mean value with a wider CI of, for example, mmHg. With such a wide CI, the population mean could be as high as 210 mmHg, which is far from the sample mean of 120 mmHg. In fact, a very wide CI in a study should be a red flag: it indicates that more data should have been collected before any serious conclusions were drawn about the population.

Remember, the narrower the CI, the more likely it is that the sample value represents the population value. n MAHER M. EL-MASRI, RN, PhD, IS AN ASSOCIATE PROFESSOR AND RESEARCH LEADERSHIP CHAIR IN THE FACULTY OF NURSINg, UNIVERSITY OF WINDSOR, IN WINDSOR, ONT. Confidence intervals: Part 1 TERMInoLogy 101 NurseONE resources on THIS TopIc EBSCO-MEDlInE full-text articles • Hildebrandt, M., Vervà¶lgyi, E., & Bender, R. (2009). Calculation of NNTs in RCTs with time-to-event outcomes: A literature review. BMC Medical Research Methodology, 9, 21. • Hildebrandt, M., Bender, R., Gehrmann, U., & Blettner, M. (2006).

Calculating confidence intervals for impact numbers. BMC Medical Research Methodology, 6, 32. • Altman, D. G. (1998). Confidence intervals for the number needed to treat. BMJ (Clinical Research Ed.), ), .

Myilibrary • Campbell, M. J., Machin, D., & Walters, S. J. (2010). Medical statistics: A textbook for the health sciences (4th ed). • Mateo, M. A., & Kirchhoff, K.

T. (Eds.). (2009). Research for advanced practice nurses: From evidence to practice. • Webb, C., & Roe, B. (Eds.). (2007). Reviewing research evidence for nursing practice: Systematic reviews. 8 CANADIAN-NURSE.COM However, users may print, download, or email articles for individual use.

Paper for above instructions

Understanding and Calculating Confidence Intervals

Introduction

Confidence intervals (CIs) are vital statistical tools widely utilized to estimate population parameters based on sample data. A confidence interval provides a range of values that is likely to contain the true value of a population parameter, such as a mean or proportion, with a certain level of confidence. The purpose of this essay is to explore the concept of confidence intervals, their interpretation, and the calculations involved in determining them.

The Concept of Confidence Intervals

At its essence, a confidence interval is derived from sample data regarding a specific population parameter. For instance, suppose a researcher is assessing the average height of adult men in a city. Instead of measuring every individual, the researcher might measure a sample of 100 men, calculate the sample mean (M), and construct a confidence interval around that mean to estimate the true average height within the entire population (Lang & Secic, 2006).
Confidence intervals are typically expressed with two numbers, the lower and upper limits, indicating the range in which the true population parameter exists. The confidence level (e.g., 90%, 95%, or 99%) signifies how certain we are that this interval leads to the actual population parameter. A 95% confidence interval, for instance, implies that there is a 95% chance that, if we were to take an infinite number of samples, 95% of the calculated intervals would contain the true population mean (Epi Info, n.d.).

Calculating Confidence Intervals

The formula for calculating the confidence interval depends on whether the standard deviation of the population is known and the sample size.

1. Confidence Interval for the Mean (µ)

When the population standard deviation is known, the confidence interval can be calculated using the formula:
\[
CI = \bar{x} \pm z_{\alpha/2} \cdot \left(\frac{\sigma}{\sqrt{n}}\right)
\]
Where:
- \(\bar{x}\) is the sample mean
- \(z_{\alpha/2}\) is the z-value corresponding to the desired confidence level
- \(\sigma\) is the population standard deviation
- \(n\) is the sample size
If the population standard deviation is unknown, the t-distribution is used instead, leading to the formula:
\[
CI = \bar{x} \pm t_{\alpha/2} \cdot \left(\frac{s}{\sqrt{n}}\right)
\]
Where:
- \(s\) is the sample standard deviation
- \(t_{\alpha/2}\) is the t-value corresponding to the desired confidence level from the t-distribution table.

2. Confidence Interval for Proportions (p)

For confidence intervals regarding population proportions, the formula is as follows:
\[
CI = \hat{p} \pm z_{\alpha/2} \cdot \sqrt{\frac{\hat{p}(1 - \hat{p})}{n}}
\]
Where:
- \(\hat{p}\) is the sample proportion.

Example Calculations

1. Confidence Interval for the Mean:
Using the provided values in the assignment:
- Sample Mean (\(\bar{x}\)): 17.3185
- Sample Standard Deviation (\(s\)): 3.4029
- Sample Size (\(n\)): 27
- Confidence Level: 0.990
Finding \(t\) for \(26\) degrees of freedom (given by \(n-1\)), we can find the corresponding value from a t-table. Assuming \(t\) is approximately \(2.779\):
\[
CI = 17.3185 \pm 2.779 \cdot \left(\frac{3.4029}{\sqrt{27}}\right)
\]
This results in a margin of error of approximately \(1.819935\) leading to limits of \(15.498565\) (Lower) and \(19.138435\) (Upper).
2. Confidence Interval for Proportions:
Using the values given:
- Sample Proportion (\(\hat{p}\)): 0.428571
- Successes: 141
- Sample Size (\(n\)): 329
- Confidence Level: 0.950
Using \(z\) as approximately \(1.960\):
\[
CI = 0.428571 \pm 1.960 \cdot \sqrt{\frac{0.428571(1 - 0.428571)}{329}}
\]
Following the calculation leads to a sample confidence interval ranging from approximately \(0.375096\) (Lower) to \(0.482046\) (Upper).

The Importance of Sample Size

Determining an appropriate sample size is crucial, as it directly impacts the confidence interval's width. A larger sample size generally leads to a more narrow confidence interval, thereby increasing the precision of our estimates. The width of the interval is also influenced by the confidence level chosen; higher confidence levels lead to wider intervals, as a greater degree of certainty requires a broader range.

Conclusion

Understanding confidence intervals is foundational in statistics and research. They provide crucial insight into the uncertainty associated with sample estimates, allowing researchers to make informed conclusions about population parameters. As discussed, confidence intervals for means and proportions involve different calculations but share the common principle of estimating the true population value from sample data. Choosing an appropriate confidence level and sample size is essential to reaching meaningful conclusions in research.

References

1. Altman, D. G. (1998). Confidence intervals for the number needed to treat. BMJ (Clinical Research Ed.).
2. Campbell, M. J., Machin, D., & Walters, S. J. (2010). Medical statistics: A textbook for the health sciences (4th ed.).
3. Epi Info. (n.d.). Confidence Intervals. Retrieved from [CDC website].
4. Hildebrandt, M., Bender, R., Gehrmann, U., & Blettner, M. (2006). Calculating confidence intervals for impact numbers. BMC Medical Research Methodology, 6, 32.
5. Lang, T.A., & Secic, M. (2006). How to report statistics in medicine (2nd ed.). Philadelphia: American College of Physicians.
6. Mateo, M. A., & Kirchhoff, K. T. (Eds.). (2009). Research for advanced practice nurses: From evidence to practice.
7. Webb, C., & Roe, B. (Eds.). (2007). Reviewing research evidence for nursing practice: Systematic reviews.
8. Hildebrandt, M., Vervà¶lgyi, E., & Bender, R. (2009). Calculation of NNTs in RCTs with time-to-event outcomes: A literature review. BMC Medical Research Methodology, 9, 21.
9. CDC. (n.d.). Confidence Intervals - A Brief Introduction.
10. M. (2012). Confidence intervals: Part 1. NurseONE.