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Spring 2015 > NUTR Capstone - Exam #1 (Part 2) > Flashcards

NUTR Capstone - Exam #1 (Part 2) Flashcards

1
Q

What is a Prospective Study?

A

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

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2
Q

What is a Cross-Sectional Study?

A

A group examined at ONE point in time

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3
Q

What is a Case-Control Study?

A

Two groups, based on the outcome

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4
Q

What are the types of OBSERVATIONAL Studies?

A
  1. Prospective
  2. Cross-Sectional;
  3. Case-Control
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5
Q

What are the types of Experimental Studies?

A
  1. Cross-Over Randomized;
  2. Randomized blinded trial (short term)
  3. Randomized binded trial (long term)
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6
Q

What is a Cross-Over Randomized Trial?

A

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

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7
Q

What is a Randomized Short, Blinded Trial?

A

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

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8
Q

What is Randomized Long, Blinded Trial?

A

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

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9
Q

What is Statistics?

A

an objective, mathematical means to interpret a collection of observations

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10
Q

How must a researcher use Statistics?

A

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)
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11
Q

What about the experiment guides the Statistical analysis?

A
  • 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
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12
Q

What are the stats for Comparative Research questions?

A
  • Do differences exist?

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

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13
Q

What are the stats for Relational Research questions?

A
  • Do correlations or associations exist?
  • Statistical analysis assesses correlations or associations (Pearson or Spearman’s rho correlations or chi-squared test)
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14
Q

What is a Comparison study?

A
  • 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?
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15
Q

What is the Null Hypothesis (H0)?:

A

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

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16
Q

What is the Alternative Hypothesis (HA)?

A

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

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17
Q

What are the errors with Comparative Studies?

A

Type I and Type II Error

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18
Q

What are Type I Errors?

A
  • REJECTING the null hypothesis when it is TRUE;

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

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19
Q

What are Type II Errors?

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

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

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20
Q

What are Variables?

A
  • Measurements/data collected

- Discrete or Continuous

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21
Q

What are Discrete Variables?

A

-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)
22
Q

What are Continuous Variables?

A

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

23
Q

How are Discrete variables reported?

A

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
24
Q

How are Continuous variables reported?

A
  • 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
25
Q

What are the different types of relationships and samples?

A
  1. Independent
  2. Dependent
    — Pairing and matching
    — Serial measurements – Examples???
    — Replicate measurements – Examples ????
26
Q

What are the problem with multiple comparisons or multiplicity?

A
  • 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.
27
Q

What is the Assumption of Normality?

A
  • 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)
28
Q

One Standard Deviations from the Median

A

60% of data

29
Q

Two Standard Deviations from the Median

A

95% of data

30
Q

Three Standard Deviations from the Median

A

99.7% of data

31
Q

What is Skewness?

A
  • 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
32
Q

What the Transformation of data?

A

Transformations: → Force the raw data into normality

33
Q

What is Raw Data?

A

NON normalized data

—Needs to be log transformed to reach normality

34
Q

What are the Nonparametric

A

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
35
Q

What are significance tests?

A

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.
36
Q

What is the general producer for statistical analysis?

A

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

37
Q

Stats: Step 1) Examine the data

A
  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
38
Q

Stats: Step 2) Estimate in Statistics

A 
Provide the reader with one or more of the following statistical descriptions: 
•Mean
•Median
•Range
•Correlation coefficient
•Relative risk
•Standard error
•Confidence interval
39
Q

Stats: Step 3) Determine the Statistical Significance

A

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

40
Q

How is the research question answered?

A

-Determine relationships and associations

41
Q

How is DISCRETE data summarized?

A

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
42
Q

What is Relative Risk?

A

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

43
Q

What is an Odds Ratio?

A

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

44
Q

How is CONTINUOUS data summarized?

A

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

45
Q

What is a Regression analysis?

A

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

46
Q

What is a correlation coefficient?

A

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

47
Q

What is a short story?

A
  • 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.”
48
Q

What is a Scientific story?

A
  • Logical sequence
  • Believable
  • Not too long
  • Not too short
  • Clear and concise
49
Q

What are the “basics” of a short story?

A
  • Scene/setting
  • Protagonist
  • Antagonist
  • Climax
  • Conclusion
  • (Optional) Stakes
50
Q

Why is Scientific Storytelling Important?:

A
  • Helps us think and ask questions
  • Provides us with a logical process to report scientific information
  • Your presentation will tell a compelling research narrative.
51
Q

What is Scientific Storytelling?

A
  • “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.”
52
Q

What are the stages of a scientific story?

A
  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?

Spring 2015 (14 decks)

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