Discuss the data distribution of the histogram

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Reference no: EM132062299

Assignment -

Multiple Choice Questions -

Question 1 - Researchers study the relationship between interpersonal violence and health in college age women. They selected an alpha value of 0.05. The researchers examined levels of social support for abused versus non-abused women. A pvalue of 0.19 is reported. Based on this information, you know:

There is a statistically significant difference in social support between the two groups.

In this study, women who were abused were statistically less likely to report social support.

This is a clinically significant result.

There is no significant difference in social support between the two groups.

Question 2 - Researchers study the relationship between taking Vitamin C and life expectancy. A pvalue of 0.43 is reported. If the researchers were incorrect about this conclusion it would be an example what?

A sampling error

A type II error

An over-enrolled study

A type I error

Question 3 - A study reports an association between feeding livestock antibiotics and drug resistance in humans. You know this means:

The study had adequate power to find the association.

The alpha value was only 0.10 which is why they reported statistical significance.

The researchers did not include enough subjects in their study.

The study was underpowered.

Question 4 - After completing the power analysis the researchers determine they need a sample size of 400 to have adequate power in their study. After enrolling subjects they have a lower response rate than anticipated and they only enroll 320. Inadequate enrollment may increase the risk of:

Statistical significance

Systemic bias

A type I error

A type II error

Question 5 - A small study reports energy drinks are associated with hyperadrenergic syndrome with an effect size of 0.7. You are funded to complete a larger study on the issue. You know:

This is a strong effect size so you will only need a small sample size to detect it

This is a small effect size so you will only need a small sample to detect it.

This is a moderate effect size.

This is a strong effect size so you will need a large sample to detect it.

Question 6 - Your patient completes a DXA scan and the report indicates her left hip bone density has a Z-score of -1.4 with a pvalue of 0.001. You know this means:

Your patient's left hip bone density is average.

Your patient's left hip bone density is significantly above average.

Your patient's left hip bone density is significantly below average.

This is a clinically significant difference.

Question 7 - Researchers study the relationship between interpersonal violence and health in college aged women. They selected an alpha value of 0.05. The researchers wanted to see if there was a significant difference in the type of primary residence (home vs. student housing) for abused versus non-abused college aged women (yes/no). What statistical test would be appropriate for this analysis?

McNemar's test

Chi-square

A cumulative frequency

A cumulative percentage

Question 8 - A pilot study examines the concurrent use of dextromethorphan and SSRIs (yes/no) and serotonin syndrome (yes/no). The alpha value was 0.10 and the power was 0.80. The pvalue was 0.03. You know this means:

Use of dextromethorphan increases the risk of serotonin syndrome.

There is no association between concurrent use of dextromethorphan and SSRIs and serotonin syndrome.

There is a statistically significant association between concurrent use of dextromethorphan and SSRIs and serotonin syndrome.

There is a clinically significant association between concurrent use of dextromethorphan and SSRIs and serotonin syndrome.

Question 9 - A study with 890 subjects examines shift worked (day/night) and back injuries (yes/no). An appropriate test to use would be:

Chi-square

dependent t-test

independent t-test

ANOVA

Question 10 - Researchers are studying individuals with a history of DVT to see if taking a daily ASA is associated with fewer repeat DVT's in this high risk population. They report a chi-square value of 158.6 with a pvalue of 0.01. They follow up with a study to examine if daily ASA versus daily warfarin is associated with fewer repeat DVT occurrences. They report a chi-square of 0.534 with a pvalue of 0.46. Based on this information what should they conclude?

Taking a daily ASA is associated with fewer repeat DVT's for those with a history of a DVT.

Taking ASA or Warfarin is not significantly associated with fewer repeat DVT's for those with a history of a DVT.

Taking Warfarin daily is significantly associated with fewer repeat DVT's for those with a history of a DVT.

Taking Warfarin daily is not significantly associated with fewer repeat DVT's for those with a history of a DVT.

Question 11 - A professor wished to determine if there is a difference between the average test grades of her students who use the resources available to them with those students who don't use the resources. The alpha value is 0.05 and the pvalue is 0.03. She should conclude:

Reject the null hypothesis. Nursing students are more likely to use the resources available.

Reject the null hypothesis because there is a statistically significant relationship between nursing students' grades and their use of available resources.

Fail to reject the null hypothesis. There is not a relationship between nurses' grades and using available resources.

Fail to reject the null hypothesis. The relationship is not clinically significant.

Question 12 - Researchers studied symptom distress and palliative care designation among a sample of 710 hospitalized patients. Controlling for age, they used a t-test to compare average distress from nausea scores in men and women. Lower scores indicated less distress from nausea. They report men had an average score of 1.02 and women had an average score of 1.79. Which statement is correct?

Men had significantly less distress from nausea.

There is a positive correlation between distress from nausea and gender.

Men had less distress from nausea on average than women but we cannot determine if this is a significant difference.

Men had half as much distress from nausea as women but we cannot determine if this is a significant difference.

Question 13 - A random sample of nurses were involved in a hand washing study at a local hospital to determine if the average residual bacterial count on hands was different for day or night nurses. The study invovles an alpha value of 0.10 and finds a value of 0.12. What should the researcher conclude?

This is a type II error.

Night 'nurses have a higher average residual bacterial count on their hands.

There is not a statistically significant difference in the residual bacterial count found on the hands of day and night nurses.

There is a statistically significant difference in the residual bacterial count found on the hands of day and night nurses.

Question 14 - Researchers studied pain among a sample of 1200 hospitalized patients. Study participants were divided into three age groups to access differences in distress from pain (scale 0-10). Which test would be appropriate?

ANOVA because three groups are being compared and the outcome variable is at a ratio level.

An independent t-test because the age groups arc not related.

A paired t-test was appropriate because the patients were all from the same hospital.

Repeat measures ANOVA because the subjects got one year older annually and they act as their own control group.

Question 15 - A study examines educational preparation and the average score on a cultural competency exam. Subjects included are nurses with an associate's degree, nurses with a baccalaureate degree, nurses with a master's degree, and nurses with a doctoral degree all of whom complete a survey of 40 questions. What test would be appropriate to determine if there is a significant difference in the average scores among the nurses with the different levels of educational preparation?

Outcome analysis

Chi-square

ANOVA

Independent t-test

Question 16 - A study utilizes ANOVA to examine the average distribution rates of an antibiotic in infants, toddlers and school age children. The results include an F-statistics that is 1.04. You know this means:

The differences between the groups are similar to the differences within the groups.

Infants distribute the antibiotic faster because they have a higher percentage of fluid in their bodies.

There is not a statistically significant difference in between the groups.

There is a 5tatstically significant difference in the average distribution rates in the three groups.

Question 17 - Researchers design a study to assess the score achieved on Beck's depression inventory before 59 patients begin a group therapy intervention and after 6 weeks, 12 weeks, and 6 months after completion. An appropriate statistical test to use would be:

t-test for dependent groups

multiple regression

t-test for independent groups

repeat measures ANOVA

Question 18 - Researchers report a significant Pearson's correlation for pain and distress (r=0.91). Which statement is correct?

As pain increases distress increases 90%.

As pain decreases distress decreases.

There is a weak positive correlation between pain and distress but it is significant.

There is a moderate positive correlation between pain and distress.

Question 19 - A study examines the relationship between total years of educational preparation and total score on a cultural competency exam among a group of 987 randomly selected nurses at your hospital. What test would be appropriate to determine if there is an association?

ANOVA

Pearson's Correlation

Dependent t-test

Independent t-test

Question 20 - A study examines the relationship between being a registered nurse (yes/no) and passing a cultural competency exam (yes/no) among a group of 987 randomly selected employees at your hospital. What test would be appropriate to determine if there is an association?

Pearson's Correlation

MeNemar's test

Chi-square

Independent t-test

Question 21 - A study examining the relationship between travel and stress reports an r=0.4 (pvalue = 0.02). You know that this means:

When people travel their stress level decreases.

There is a weak positive correlation between the variables in the study.

As travel increases there is a 40% increase in stress.

There is a significant positive correlation between travel and stress.

Question 22 - A study examining the relationship between the number of quiet hours and patient satisfaction reports r = 0.6, pvalue = 0.02. You know this means:

For each additional quiet hour patient satisfaction increases 60%.

36% of the variance in patient satisfaction is due to differences in the number of quiet hours.

There is a weak relationship between the number of quiet hours and patient satisfaction.

Because the pvalue is less than the r value there is a significant relationship between the number of quiet hours and patient satisfaction.

Question 23 - A researcher is examining the relationship between the number of surgical errors made and experience (measured in years) in a sample of 60 residents at your hospital. An appropriate test would be:

Pearson's correlation coefficient

Spearman's correlation coefficient

Independent t-test

ANOVA

Question 24 - A researcher reports that performance was significantly correlated with overall engagement among nurses enrolled in an online degree program (r = 0.8). You know this means:

As engagement goes up performance goes up.

The p value is less than the alpha value.

As performance goes up engagement goes up.

All of these answers are correct.

Question 25 - A study examines the relationship between years of educational preparation, language spoken, age, primary nursing role, race and ethnicity and total score on a cultural competency exam among a group of 987 randomly selected nurses at your hospital. What test would be appropriate to determine there is an association?

Pearson's correlation

Multiple regression

Independent t-test

ANOVA

Question 26 - A researcher is studying 378 nurses enrolled in an online RN to BSN completion program and analyzing how age, level of engagement, motivation and time spent studying impact the final est score. When she enters age and motivation into the regression model the R-square change associated with each is NOT significant. You would recommend:

Rechecking the math, this is a type II error.

Only including motivation and time spent studying.

Not including age and motivation in the regression model.

Decreasing the sample size.

Question 27 - A psychiatric nurse practitioner completes a study examining psychological distress scores, hours spent sleeping, and the number of visitors to see if these variables impact minutes spent in ritualistic behavior among patients diagnosed with obsessive compulsive disorder. She reports the following information. What statement is true?

 

Beta coefficient

Significance

psychological distress

11.511

0.000

sleeping

-4.735

0.020

visitors

3.220

0.410

All of the variables are significant predictors.

For each additional hour of sleep ritualistic behaviors are decreased by 2%.

Sleeping significantly impacts the number of minutes spent in ritualistic behavior.

The most significant predictor is the number of visitors.

Question 28 - A psychiatric nurse practitioner completes a study examining psychological distress scores (DS), hours spent exercising (X), and number of counseling sessions (C) to see if these variables impact minutes spent in ritualistic behavior among patients diagnosed with obsessive compulsive disorder. She reports the following regression equation.

Y = 59 + 3.98(DS) - 2.89(X) - 4.5(C)

If a patient has a distress score of 5, spends 2 hours exercising and attend a counseling session you would expect to see about how many minutes of ritualistic behavior?

29.5

68.6

unable to determine

9.6

Question 29 - A nurse researcher studies the impact of medication and exercise on HgA1C levels and reports that medication and exercise significantly decreases HgA1C levels. The R-square associated with the model is 0.83. You know this means:

including exercise in the model increased the error of the prediction.

medication and exercise explain 17% of the variance in HgA1C levels.

medication and exercise explain 83% of the variance in HgA1C lelves.

medication and exercise are not significant predictors.

Question 30 - Researchers study the relationship between interpersonal violence and health in college aged omen. The researchers planned to examine the average score on a psychological distress scale and compare the score for abused versus non-abused women. What would be an appropriate test to consider?

Chi-square test

t-test for independent groups

Dependent t-test

McNemar's test

Short Answer Questions -

Question 31 - The following table provides frequencies of the tip distribution for a waitress at the Pizza Cabanna for two weeks in August. On your own paper, draw a histogram.

a) Discuss the data distribution of the histogram.

b) Would the researcher need to be concerned about the distribution? Why/why not.

c) What tip class had the most tips?

d) How many tips did the waitress have that were less than $8?

e) What percentage of tips were above $10?

Tip Class

Frequency

$0-1

1

$2-3

5

$4-5

9

$6-7

18

$8-9

22

$10-11

20

$12-13

14

$14-15

10

$16-17

6

$18-19

3

$20 or more

2

Question 32 - The scatterplot below shows the gestation period (in days) of different mammals and their longevity (in years).

a) Which variable is the explanatory (independent) variable?

b) Which variable is the response (dependent) variable?

c) Discuss whether there appears to be an association between the variables?

d) What are possible confounding variables that might influence this relationship?

2280_figure.png

Question 33 - Below is the Excel output comparing the stress levels of mice that are in either a standard environment or an enriched environment.

Identify for this scenario:

a) the null and alternative hypotheses.

b) the decision rule based on an alpha value of 0.05

c) a contextual conclusion regarding the stress levels of mice in the different environments.

 

Enriched

Standard

Mean

231.7142857

438.7142857

Variance

5073.238095

1419.904762

Observation

7

7

Hypothesized Mean Difference

0

 

df

9

 

t Stat

-6.796602744

 

P(T<=t) one-tail

3.96787E-05

 

t Critical one-tail

1.833112933

 

P(T<=t) two-tail

7.93573E-05

 

t Critical two-tail

2.262157163

 

Question 34 - 143 countries of the world were divided up into 7 regions: North America, South America, Western Europe, Eastern Europe, Asia, Africa, and South Pacific. The Excel sheet shows the output from the data analysis comparing the happiness index for each region.

a) What analysis was conducted?

b) What are the null and alternative hypotheses?

c) What is the decision rule based on an alpha value of 0.05?

d) What is the conclusion about the happiness indexes between the regions?

SUMMARY

Groups

Count

Sum

Average

Variance

1

24

165.95

6.914686

0.461022

2

24

181.13

7.577137

0.279923

3

16

95.69

5.980436

0.724304

4

33

133.64

4.049804

0.559059

5

7

39.06

5.580688

0.099670

6

12

75.64

6.303320

0.450761

7

27

154.77

5.732129

0.336421

 

ANOVA

Source of Variation

SS

df

MS

F

P-value

F crit

Between Groups

206.2866664

6

34.38111106

77.80144685

1.56E-41

2.165882

Within Groups

60.09953919

136

0.441908376

 

 

 

Total

266.3862055

142

 

 

 

 

Question 35 - The nigh time temperature and the number of chirps for 10 crickets were recorded. The Excel output for the analysis is provided below.

 

Temperature

Chirps

Temperature

1

 

Chirps

0.9906

1

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.990624882

R Square

0.981337658

Adjusted R Square

0.977605189

Standard Error

6.561272077

Observation

7

 

ANOVA

 

df

SS

MS

F

Significance F

Regression

1

11318.74854

11318.75

262.9192094

1.62634E-05

Residual

5

215.2514563

43.050529

 

 

Total

6

11534

 

 

 

 

Coefficients

Standard Error

t Stat

P-value

 

Intercept

-157.8165049

18.10590819

-8.7163

0.000329054

 

Temperature

4.254368932

0.262375929

16.21478

1.62634E-05

 

a) What is the explanatory (independent) variable?

b) What is the response (dependent) variable?

c) Discuss the strength and direction of the correlation coefficient.

d) Is the regression model statistically significant?

e) What is the regression line that could be used to predict the number of chirps?

f) If the nigh time temperature was 20 degrees, what number of chirps can we expect?

Reference no: EM132062299

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