1 / 18

Observations

Observations. DI Water 40% Ethanol. Statement of Problem. Why does the pigment look faded with 40% ethanol?. Hypotheses. Ha1 Ethanol enters the cell and breaks down the pigment. Ha2 Ethanol breaks down the cell membrane releasing contents of the cell including the pigment.

halden
Download Presentation

Observations

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Observations • DI Water • 40% Ethanol

  2. Statement of Problem • Why does the pigment look faded with 40% ethanol?

  3. Hypotheses • Ha1 Ethanol enters the cell and breaks down the pigment. • Ha2 Ethanol breaks down the cell membrane releasing contents of the cell including the pigment.

  4. Methods • Control = chopped onions added to water. • Treatment = chopped onions added to 40% ethanol. • Measure amount of pigment in two solutions with spectrometer.

  5. Spectrometer Measures light intensity of different wavelengths (colors) Sensor

  6. Predictions • Ha1 Ethanol enters the cell and breaks down the pigment. • Ha2 Ethanol breaks down the cell membrane releasing contents of the cell including the pigment. • If Ha1, then the control solution will have the same or more pigment than the treatment. • If Ha2, then the control solution will have less pigment than the treatment.

  7. Measures of Central Tendency 3 4 4 5 6 7 7 7 7 8 8 Mean = (sum)/n = 66/11 = 6 Median = center value = 7 *If n is even, median = avg. of the two middle numbers ex. 1 4 4 6 9 15 median = 5

  8. Indices Mathematical manipulations of the data to assist with interpretation Ex. Diet Studies typically record: N = numerical percentage M = mass percentage F = frequency of occurrence Index of Relative Importance = (N+M)*F Another example: Shannon Weaver’s Index of Diversity

  9. Graphs t Continuous independent variables

  10. Graphs Cascades frog stomach contents at fish-containing and fishless lakes Discrete independent variables Bar graphs need error bars

  11. Graphs • X-axis is the independent variable • Y- axis is the dependent variable • Need titles or legends • Bar graphs need error bars, usually +/- SE • SE=Standard Error • Onto stats…

  12. Statistics for this lab Procedure #2 Bar graphs need to have error bars Error bars will represent the standard error (SE) 3 4 4 5 6 7 7 7 7 8 8 Dataset A Mean = 66/11 = 6 -200 -58 -20 -15 4 7 7 40 43 70 188 Dataset B Mean = 66/11 = 6 What’s the difference? SEA = 0.52 SEB = 28.18

  13. Standard Error SE represents the amount of variation within a sample SE = (standard deviation) / (sqrt(N)) N is the sample size Standard deviation:

  14. T-tests & Statistical Hypotheses Ho: Treatment (alcohol) absorption = control (water) absorption. Ha: Treatment absorption ≠ control absorption. T-tests use means and standard errors to determine whether two discrete groups are significantly different.

  15. T-tests P value  Probability(type I error) Level of significance = P “Statistically significant” Type I error: rejecting a true null hypothesis Type II error: accepting a false null hypothesis Generally, scientists try to minimize the probability of making a type I error.

  16. T-tests Ho: Treatment (alcohol) absorption = control (water) absorption. Ha: Treatment absorption ≠ control absorption. ex. if P=0.48 48% chance that we are wrong to reject Ho. Thus, we do not reject Ho. P<0.05 acceptable for most things ex. If P=0.03, we would reject Ho and accept Ha.

More Related