midterm exam coverage Flashcards by entamoeba pusomanni

it is the equilibrium constant for a solid substance dissolving in an aqueous solution

solubility product constant (Ksp)

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it is the concentration of solute in a saturated aqueous solution

molar solubility

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if an external stress is applied to a system at equilibrium, the system adjusts in such a way that the stress is partially offset as the system reaches a new equilibrium position

le chatelier’s principle

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change in equilibrium: increase concentration of products

shift to left

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change in equilibrium: decrease concentration of products

shift to right

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change in equilibrium: increase concentration of reactants

shifts to right

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change in equilibrium: decrease concentration of reactants

shifts to left

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change: increase in pressure

side with fewest moles of gas

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change: decrease pressure

side with most moles of gas

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change: decrease volume

side with fewest moles of gas

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change: increase volume

side with most moles of gas

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used to judge the quality of experimental measurements

statistical calculations

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indicates the closeness of the measurement to its true or accepted value

accuracy

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describes the reproducibility of measurements or the closeness of the results

precision

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causes data to be scattered more or less symmetrically around a mean value

random error / indeterminate

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causes the mean of a set of data to differ from the accepted value

systematic / determinate error

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this error occasionally occurs, is often large, and may cause a result to be either high or low.

it also leads to outliers, results that appear different from the data set

gross error

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systematic error: caused by imperfections in measuring devices and instabilities in their components

instrument error

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systematic error: nonideal chemical or physical behavior of the reagents and reactions upon which analysis is based

method error

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systematic error: measurements requiring personal judgment (personal limitations).

personal error

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systematic errors can be either?

constant errors
proportional errors

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type of systematic error: independent of the size of the sample being analyzed

constant errors

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type of systematic error: increased or decreased in proportion to the size of the sample.

proportional errors

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what are the 3 ways to detect systematic errors?

Analysis of reference standards
Analysis of the blank samples
Varying the sample size

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what is denoted by s

standard deviation

the absolute value of the coefficient of variation

relative standard deviation

the measure of the relative dispersion of data points in a data series around the mean

coefficient of variation

describe the precision of a set of replicate results. it is the difference between the largest value in the set and the smallest.

spread / range (w)

an expression of the uncertainty of a measurement expressed in plus-or-minus the last digit

absolute uncertainty

ratio of the absolute uncertainty in a measurement to the value of the measurement. It can be expressed in pph, ppt or ppm

relative uncertainty

the variance of a sum or difference is equal to the sum of the individual variances, which demonstrates how the errors propagate

propagation of errors

the weighted average of standard deviations for 2 or more groups commonly used in t-tests and ANOVA it can be used to calculate repeatability and within-lab reproducibility

pooled standard deviation

a numerical interval around an experimentally determined mean that contains μ with a certain degree of probability can be determined by the normal distribution curve

confidence level

what is the numerical magnitude of the confidence limit?

confidence interval

what is the probability of a result outside the confidence interval?

significance level

a measurement that is not consistent with the other set of measurements

outlier

One of the most common significance tests for identifying an outlier Use if there are no known reasons for an outlier data point

dixon's Q test

Qexp in Q test stands for?

test statistic

Xi in Q test represents?

measure of a potential outlier

# Q Test Hypothesis Testing there are no outliers present in the data

null hypothesis | Ho

# Q Test Hypothesis Testing there is an outlier present in the data

alternative hypothesis | Ha

# Q Test Hypothesis Testing if Qexp > Qcrit

reject Ho, accept Ha | meaning, may outlier na present talaga

# Q Test Hypothesis Testing if Qexp < Qcrit

fail to reject Ho | meaning, walang outlier

steps to determine if there is an outlier using Q test

1. state the null and alternative hypothesis 2. identify the test and the test statistic to be used 3. state the decision rule based on the rejection region 4. compute the Qexp based on the given values 5. apply the decision rule and make a decision 6. interpret the results based on the decision and make a conclusion

recommended by the International Standards Organization (ISO) and the American Society for Testing and Materials (ASTM) use to check suspected outliers in a normally distributed data

grubb's test

Gexp stands for?

the test statistic

# Grubb's Test Hypothesis Testing if Gexp > Gcrit?

then reject Ho, accept Ha | meaning, may outlier

# Grubb's Test Hypothesis Testing if Gexp < Gcrit?

then fail to reject Ha | walang outlier

steps to use grubb's test

1. state the null and alternative hypothesis 2. identify the test and the test statistic to be used 3. state the decision rule based on the rejection region 4. compute the mean, standard deviation, Gexp based on the given values 5. apply the decision rule and make a decision 6. interpret the results based on the decision and make a conclusion

accounts for the variability given by the sample standard deviation/s used in determining significant difference in means of smaller samples

T-statistic / T-Test

2 types of t-test

unpaired and paired samples

# T-Test Hypothesis Testing there is no significant difference between the means | for unpaired samples

null hypothesis | Ho

# T-Test Hypothesis Testing 2 types of alternative hypothesis

one-tailed two-tailed

# T-Test Hypothesis Testing u1 ≠ u2; there is a significant difference between the mean

two-tailed | Ha

# T-Test Hypothesis Testing u1 > u2; there is a significant difference between the means, the *mean of the 1st data set is greater* than the mean of the 2nd data set

one-tailed

# T-Test Hypothesis Testing u1 < u2 in an alternative hypothesis means that...

there is a significant difference between the means, the mean of the 1st data set is less than the mean of the 2nd data se

critical values for tcrit based on ____ degrees of freedom

N - 2

steps in using t-test for unpaired samples

1. state the null and alternative hypothesis 2. identify the test and the test statistic to be used 3. state the decision rule based on the rejection region 4. solve for the test statistic, t based on the given values 5. apply the decision rule and make a decision 6. interpret the results based on the decision and make a conclusion

it is for two samples with data sets that are collected in the same manner and can be matched with one another

t-test paired samples

# T-Test Hypothesis Testing (Paired) ud = △0; there is no significant mean difference between pairs

null hypothesis | Ho

# T-Test for Paired Alternative Hypothesis (Ha) ud ≠ △0 | There is a significant mean difference between pairs

two-tailed

# T-Test for Paired Ha ud > △0 | one-tailed

The mean significant difference between pairs is greater than zero

# T-Test for Paired Ha ud < △0 | one-tailed

The mean significant difference between pairs is less than zero

steps to use t-test

1. state the null and alternative hypothesis 2. identify the test and the test statistic to be used 3. state the decision rule based on the rejection region 4. solve for the test statistic and t based on the given values 5. apply the decision rule and make a decision 6. interpret the results based on the decision and make a conclusion