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FNH 325 > Slide Content - Lessons > Flashcards

Slide Content - Lessons Flashcards

1
Q

What is a credible source?

A

Credible sources are reliable sources that provide information that one can believe to be true.

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2
Q

What are primary sources?

A

Eyewitness accounts or as close to the original source as possible.
* Autobiographies
* Research papers
* Government documents
* Newspapers
* Patents
* Videos
* Interviews

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3
Q

What are secondary sources?

A

Interpretations and analyses based on primary sources
* Biographies
* Review papers
* Textbooks
* Encyclopedias
* Blog posts
* Wikipedia

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4
Q

Why would you only want to search abstracts? (pro/con)

A
  • Pro: results are likely more relevant to the search because the term is present in the abstract
  • Con: may miss some tangentially related but relavent papers
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5
Q

Discuss Boolean operators. [6]

A
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6
Q

What is a biological replicate?

A
  • Involves testing different independent samples
  • Evaluates variability between samples
  • True replicates
  • Can be used directly for statistical analyses
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7
Q

What is a technical replicate?

A
  • Involves testing the same sample multiple times
  • Evaluates the variability within a specific test, sample, person
  • Not true replicates
  • Values are averaged prior to statistical analyses
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8
Q

Why are technical replicates averaged?

A
  • In the case of ANOVA, a non-averaged technical replicate would:
    • Be treated as an extra independent sample which is incorrect.
    • Increase the chance of a type-1 error (finding something to be statistically significant when it is not)
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9
Q

Differentiate between independent and dependent variables.

A

Independent: fixed
Dependent: the response (i.e., depends on the independent variable)

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10
Q

What does a standard curve require? [3]

A
  1. At least 6 concentrations of a known standard (should be evenly spaced within linear range of assay; standard should represent/resemble analyte being measured)
  2. Appropriate blank (usually reagents with no sample or standard)
  3. Sample (measurement must fall within range of standard curve; good to preapre several dilutions)
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11
Q

In this example:
How much of each standard concentration do you need?
How much of the fish sample do you need?
How much total BCA reagent do you need?

A

Standard concentration: 10 uL x 3 = 30 uL
Sample: 10 uL x 3 = 30 uL
Reagent: (6 standards + 1 sample) x 200 uL x 3 replicates = 4200 uL

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12
Q

Fill in the table – choose 6 equally spaced dilutions between 0 and 2 mg/mL including 0 mg/mL as one of the 6 standards. Prepare 1 mL of each standard

2.0 mg/mL standard

A

I

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13
Q

Now, let’s prepare 2 dilutions of the fish sample:
* Fish are known to contain between 20 – 30 g protein/100 g of fish
* The protein extraction method requires us to homogenize 25 g of fish in
100 mL of water
* What is the possible protein concentration range in this homogenous solution?

A
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14
Q
A
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15
Q
A

No outliers
Q-values < Q-crit

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16
Q

What are 3 things to consider when calculation dilution factors?

A
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17
Q

What is the dilution and dilution factor?

A
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18
Q
A

2905000
6.46 log CFU/g aerobic microbes

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19
Q
A

24250
4.38 log CFU/g coliforms

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20
Q
A

<100
<2 log CFU/g Salmonella

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21
Q

What is accuracy?

A

Accuracy is the measure of how closely an experimental value approximates the “true” or correct value.

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22
Q

What is precision?

A

Measures how well biological replicates agree with one another, regardless of whether or not they represent the “true” value

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23
Q

What is repeatability?

A

Measures how close replicate results are when a test is done at different times in the same lab by the same person using the same equipment

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24
Q

What is reproducibility?

A

Measures how close results are when carried out in different labs and/or with different instruments.

25
Q

Compare standard deviation and coefficient of variation.

A
26
Q

What digits are always significant?

A
  • Non-zero figures
  • All zeros used after a decimal
  • Zeros between two other significant figures
27
Q

What figures are not-significant?

A

Zeroes preceding non zero digits in decimals
Terminal zeros may be signifiant in whole numbers when specified

28
Q

What are addition/substraction sig fig rules?

A

The number of decimal places in the answer should be the same as the least number of decimal places in any of the numbers being added or subtracted (least precise number)

29
Q

What are multiplication/division/squaring/square root sig fig rules?

A

The number of sig figs in answer should be equal to the least number of sig figs in any one number used.

30
Q

What are sig fig conventions regarding the mean?

A
  • The mean of the dataset cannot be more accurate than the original measurements.
  • But if original measurements do not have any decimal places, one decimal place is allowed
31
Q

What are sig fig conventions for SD?

A
  • usually has the same number of sig figs as the mean
  • However, if the SD is from a very precise data set, keep 1 sig fig
32
Q

How many sig figs in r^2?

A

2 decimal places

33
Q

How many sig figs in absorbance readings?

A

No more than 4 decimal places, or use as many decimal places as the reading.

34
Q

How many sig figs for concentrations?

A

Usually 2 decimal places

35
Q

How many sig figs for log CFU/g values?

A

Use 2 decimal places

36
Q

Calculate the mean, SD, and %CV for the following data and report them using correct sig figs and rounding rules:
8.255, 8.256, 8.254, 8.256

A

Note you have to apply multiplication rule to %CV.

37
Q

What is the difference between a type 1 and type 2 error?

A
38
Q

What are numeric variables?

A
  • Continuous (infinte set of values, e.g., pH)
  • Discrete (finite numbers with given interval, e.g., ranking sweetness on 10 point scale)
39
Q

What are categorical variables?

A
  • Nominal (no order e.g., type of flour)
  • Ordinal (values can be ranked e.g., Likert scale)
40
Q

What is the null hypothesis?

A
  • States there is no difference between two means or between a mean and a hypothesized value
41
Q

What is the alternative hypothesis?

A

States that there is a difference between two means or between a mean and a hypothesized value

42
Q

What is the p-value?

A
  • Probability of obtaining the observed results, assuming the null hypothesis is true.
  • Alpha sets standard for how extreme data must be before we can reject the null
  • The p-value indicates how extreme data is
  • P-value is compared to alpha to determine if we can reject the null hypothesis.
43
Q

When do we use parametric tests?

A
  • Use when dependent variable is continuous
  • Assume underlying normal distribution and equal variance
44
Q

What are non-parametric tests?

A

Must be used when dependent variable is categorical or continuous data if non normal distribution
Not as statistically powerful as parametric tests since it uses ranked data and not actual data values

45
Q

What types of parametric tests are there?

A
  • Measures of association (linear regression and correlation)
  • Comparison of means (t-test, one-way/two-way ANOVA)
46
Q

What is linear regression?

A

Predicts the values of a dependent variable based on the values of the independent variable.

47
Q

What is correlation?

A

Tests strength of an association between 2 dependent variables.

48
Q

What does t-test compare?

A

Means of 2 groups

49
Q

What does one-way ANOVA compare?

A

Compares the means of >2 groups (levels) within the same independent variable (Factor)

50
Q

What does two-way ANOVA compare?

A

Compares the means of 2 or more groups (levels) within 2 independent variables (factors)
Determines if there is an interaction between independent variables on the dependent variable

51
Q

What is a one-sample t-test?

A

Tests the mean of a single group against a known value

52
Q

What is an independent t-test?

A

Compares the means of two independent groups.

53
Q

What is a paired t-test?

A

Compares the means from the same group at different times or under different conditions.

54
Q

When would you use a one-tailed t-test?

A

Sample mean is expected to be different from the other sample in only one direction.

55
Q

When would you use a two-tailed t-test?

A

Sample mean is expected to be different from the other sample, without an expectation of the direction

56
Q

Which is more powerful and why?
One-tailed/two tailed t-test

A

One tailed; smaller change from mean is required to achieve significance because all alpha is in one tail

57
Q

What is Fishers LSD?

A
  • Post-hoc testing to determine which levels actually differ if ANOVA indicates significance
58
Q

Why not run several t-tests instead of a one-way ANOVA?

A
  • Every time you conduct a t-test there is a chance that you will make a Type I error.
  • This error is usually 5%. By running two t-tests on the same data you will have increased your chance of “making a mistake” to 10%.
  • An ANOVA controls for these errors so that the Type I error remains at 5%.

FNH 325 (5 decks)

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