NUTR Capstone - Exam #1 (Part 2)

Question 1

What is a Prospective Study?

Answer 1

A group FREE of the disease or outcome of interest is followed over time

Question 2

What is a Cross-Sectional Study?

Answer 2

A group examined at ONE point in time

Question 3

What is a Case-Control Study?

Answer 3

Two groups, based on the outcome

Question 4

What are the types of OBSERVATIONAL Studies?

Answer 4

1. Prospective
2. Cross-Sectional;
3. Case-Control

Question 5

What are the types of Experimental Studies?

Answer 5

1. Cross-Over Randomized;
2. Randomized blinded trial (short term)
3. Randomized binded trial (long term)

Question 6

What is a Cross-Over Randomized Trial?

Answer 6

Two groups created by a random process, one group starts placebo and the other in a treatment….washout period….treatments switch groups

Question 7

What is a Randomized Short, Blinded Trial?

Answer 7

Two groups created by a random process, one group gets a placebo and the other receives treatment — days, weeks, months

Question 8

What is Randomized Long, Blinded Trial?

Answer 8

Two groups created by a random process, one group gets a placebo and the other receives treatment — several years

Question 9

What is Statistics?

Answer 9

an objective, mathematical means to interpret a collection of observations

Question 10

How must a researcher use Statistics?

Answer 10

Researchers must use statistics COMPETENTLY:

• Use the right test(s) (need to understand basic theories)
• Apply them correctly
• Interpret the results appropriately
• Know when to consult a statistician for assistance (best at the beginning)

Question 11

What about the experiment guides the Statistical analysis?

Answer 11

• Research question
• Scale of measurement in which the data are (data are always plural) collected
• Relationship among samples
• Number of samples evaluated
• Test’s assumption about the normal distribution
• Whether one- or two-sided test for significance

Question 12

What are the stats for Comparative Research questions?

Answer 12

• Do differences exist?

- Statistical tests detect differences in means or medians (t-tests or Wilcoxon rank sum test)

Question 13

What are the stats for Relational Research questions?

Answer 13

• Do correlations or associations exist?
• Statistical analysis assesses correlations or associations (Pearson or Spearman’s rho correlations or chi-squared test)

Question 14

What is a Comparison study?

Answer 14

• Scientific “intuition” the researcher has about the study outcome;
• Statistics provide the means to evaluate the data and ultimately determine whether to accept or reject the hypothesis… is it true or not?

Question 15

What is the Null Hypothesis (H0)?:

Answer 15

“there is no difference between population means, no relationship between two variables” (H0 = µ1 - µ2 =0)

Question 16

What is the Alternative Hypothesis (HA)?

Answer 16

Logical state of reality that MUST exist if the null hypothesis is not true (H0 = µ1 - µ2 ≠0)

Question 17

What are the errors with Comparative Studies?

Answer 17

Type I and Type II Error

Question 18

What are Type I Errors?

Answer 18

• REJECTING the null hypothesis when it is TRUE;

- The probability of rejecting a true null hypothesis is equal to the alpha level.

Question 19

What are Type II Errors?

Answer 19

• Accepting the null hypothesis when it is not true.;

- The probability of accepting the null hypothesis when it is false is the beta value.

Question 20

What are Variables?

Answer 20

• Measurements/data collected

- Discrete or Continuous

Question 21

What are Discrete Variables?

Answer 21

-Discrete random variables (values for which a few possible values exist);

1. NOMINAL (non-ordered)(with 2 categories = binary);
2. ORDINAL (ordered by categories but the space between the categories is undefined)

Question 22

What are Continuous Variables?

Answer 22

Continuous random variables (variables with a numerical meaning and the space between the values is defined and can be measured)

Question 23

How are Discrete variables reported?

Answer 23

Discrete (values for which a few possible values exist) = Reported as frequency/proportions (numbers/percentages)

EX:

• Binary data
• Nominal but not binary
• Ordinal data

Reported as =

1. Relative risk (RR) – cohort or prospective design
2. Odds ratio (OR) – cross-sectional or case-control

Question 24

How are Continuous variables reported?

Answer 24

• Continuous (variables with a numerical meaning and the space between the values is defined and can be measured)
  1. Mean (average)
  2. Median (middle score)
  3. Mode (most common score)
  4. Standard deviation (SD) or range
  5. Interquartile range

Question 25

What are the different types of relationships and samples?

Answer 25

1. Independent 2. Dependent — Pairing and matching — Serial measurements – Examples??? — Replicate measurements – Examples ????

Question 26

What are the problem with multiple comparisons or multiplicity?

Answer 26

- As the number of groups increase, the possible pairwise comparisons increase. - This increases the chance of finding a spurious significant result. - Have to be careful when making many comparisons. The differences might be seen due to chance. - Statistician correct by lowering the alpha level indicating significance.

Question 27

What is the Assumption of Normality?

Answer 27

- The validity of many statistical tests depends upon the assumption that the data is normally distributed and that the variability within groups is similar.; - Such tests are termed parametric tests; - Mean, Median and Mode are ALL the same (at 0 on normalized scale)

Question 28

One Standard Deviations from the Median

Answer 28

60% of data

Question 29

Two Standard Deviations from the Median

Answer 29

95% of data

Question 30

Three Standard Deviations from the Median

Answer 30

99.7% of data

Question 31

What is Skewness?

Answer 31

- Degree of departure from symmetry of a distribution. → Skewness pulls the MEDIAN from center; - POSITIVELY skewed distribution = has a "tail“ pulled in the positive direction - NEGATIVELY skewed distribution = has a "tail" pulled in the negative direction

Question 32

What the Transformation of data?

Answer 32

Transformations: → Force the raw data into normality

Question 33

What is Raw Data?

Answer 33

NON normalized data —Needs to be log transformed to reach normality

Question 34

What are the Nonparametric

Answer 34

Nonparametric or distribution-free statistical methods do not depend on having a normal distribution and can be used with skewed data or with categorical data. - Spearman’s rho - Mann-Whitney - Wilcoxon Test

Question 35

What are significance tests?

Answer 35

Departure from the mean or other parameter of interest can occur in two possible directions. 1. A one-sided significance test evaluates departures in only one direction. 2. A two-sided significance test evaluates departures in both directions.

Question 36

What is the general producer for statistical analysis?

Answer 36

Step 1: Create Statistical Summaries (Examine the data) Step 2: Estimate the Statistics Step 3: Assess the Statistical Significance

Question 37

Stats: Step 1) Examine the data

Answer 37

1. Plot the data → Examine its shape 2. Summarize the data — Discrete observations → Provide the frequency — Continuous observations → Create histograms 3. Determine the standard deviation — Provide the mean ± SD if normally distributed — Provide the mean, median and range if not normally distributed

Question 38

Stats: Step 2) Estimate in Statistics

Answer 38

``` Provide the reader with one or more of the following statistical descriptions: •Mean •Median •Range •Correlation coefficient •Relative risk •Standard error •Confidence interval ```

Question 39

Stats: Step 3) Determine the Statistical Significance

Answer 39

Test the hypothesis → Provide the reader with the level of significance (p < 0.05 for example)

Question 40

How is the research question answered?

Answer 40

-Determine relationships and associations

Question 41

How is DISCRETE data summarized?

Answer 41

Discrete data: Comparison of PROPORTIONS = - Construct row x column table - Association assessed with chi-squared - Strength of association evaluated with relative risk (cohort or prospective design) or odds ratio (case-control or cross-sectional design). Both measure the degree of association between a particular factor and an outcome event such as death

Question 42

What is Relative Risk?

Answer 42

Relative Risk= Ratio of two sample proportions= p1/p2; EX: Relative Risk = 1.82 → Describes the proportion = The placebo sample proportion of MI events 82% greater than the Aspirin sample

Question 43

What is an Odds Ratio?

Answer 43

Odds Ratio= Ratio of the odds of two sample proportions odds1/odds2; -Note: odds= probability of the event occurring / probability of the event not occurring EX: Odds Ratio = 1.83 → Describes the odds between two the two groups; Those taking the placebo had an 83% greater odds of MI versus those taking Aspirin

Question 44

How is CONTINUOUS data summarized?

Answer 44

Explore with scatter plot and summarize with linear regression or correlation coefficients

Question 45

What is a Regression analysis?

Answer 45

Regression analysis is used most commonly to quantify the association between two variables and make predictions based on the linear relationship.

Question 46

What is a correlation coefficient?

Answer 46

Correlation coefficients measures the degree of linear association between two variables.

Question 47

What is a short story?

Answer 47

- Describes a logical sequence of events surrounding a main character’s attempt to solve a problem - Scientific storytelling centers on the resolution of an “unknown.”

Question 48

What is a Scientific story?

Answer 48

- Logical sequence - Believable - Not too long - Not too short - Clear and concise

Question 49

What are the “basics” of a short story?

Answer 49

- Scene/setting - Protagonist - Antagonist - Climax - Conclusion - (Optional) Stakes

Question 50

Why is Scientific Storytelling Important?:

Answer 50

- Helps us think and ask questions - Provides us with a logical process to report scientific information - Your presentation will tell a compelling research narrative.

Question 51

What is Scientific Storytelling?

Answer 51

- “focuses on the resolution of an ‘unknown’ which is something that has never been discovered, unveiled, or revealed in the history of the world.” - “focuses on a protagonist that undergoes a series of experiments in a step-wise manner increasing the tension in order to reach a climax or climatic experiment.”

Question 52

What are the stages of a scientific story?

Answer 52

1. Set the scene – (Introduction) “Present the main character with a scientific problem in the backdrop of a fully fleshed-out scene.” 2. Increasing tension/rising action – (Subjects and methods) What do your findings say about the association of your topic with the problem? 3. Climax – (Results & Figures) Summarize the findings. 4. Falling action – (Results and Figures) Describe how the summary of the findings are associated with solving the problem. 5. Resolution – (Discussion/Conclusion) How do these findings impact human health?