Composing is Essential!.


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Category: Animals / Pets
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performed outside a living life form in a controlled domain (ex ... impact of distinctive amounts of manure (IV) on how your home plants develop (DV) ...
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Composing is Important! Suggested perusing: Clean, Well-lit Sentences: A Guide to Avoiding the Most Common Errors in Grammar and Punctuation by Janis Bell

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Writing is Important! Suggested perusing: Eats Shoots and Leaves: The Zero Tolerance Approach to Punctuation by Lynne Truss

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Biology Lab Background III/Properties of Light September 15, 2008 Overview of Microscopy Dr. Behonick

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Topics for now … Biology Lab Background III Experimental Design Types of Data Properties of Light

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Experimental configuration

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The Scientific Method Make Observation(s) from http://asweknowit.net/MIDDLE_SCH/DWA_7_scientific_method.htm

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Types of examinations in vitro "inside the glass" performed outside a living creature in a controlled domain (ex = in a test tube) in vivo "inside the living" performed in/on living tissue of in place life form ex vivo "out of the living" performed in/on living tissue in fake environment outside life form from which it was collected (ex = cell society) in silico p erformed altogether on PC or by PC reproduction

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Variables variable = what is measured or controlled in an analysis free variable = variable you have control over, what you can pick and control (value(s) you are controlling, otherwise called "controlled variable") subordinate variable = what you measure in test (what is influenced amid investigation, reacts to autonomous variable)

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Examples impact of various dosages of a medication (IV) on seriousness of sickness indications (DV) impact of various amounts of manure (IV) on how your home plants develop (DV) would need to control different variables like water, soil, size of pot, time in sun, and so forth impact of various water temperatures (IV) on how quick a sugar solid shape will break up (DV) impact of paper towel brand (IV) on how much water can be doused up with one paper towel sheet

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Cause & Effect change in ward variable (impact) control of free variable (cause)

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Controlling for Bias blindedness - controlling for cognizant/oblivious inclination in exploration misleading impact = subject getting fake treatment reports change in manifestations (notwithstanding absence of genuine substance treatment) because of desire or conviction that it will work spectator predisposition = mistake in perception/estimation when onlookers overemphasize practices they hope to discover & neglect to notice conduct they don\'t expect

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Controlling for Bias single-visually impaired study = subjects are blinded however experimenters are not ex = subject does not know whether accepting medication or sugar pill experimentor either can\'t be blinded because of outline of study or doesn\'t should be on the grounds that can\'t present further inclination twofold visually impaired study = both subjects and experimenters are blinded subjects haphazardly doled out to gatherings, experimenters don\'t know assignments expert rundown of gathering assignments kept by outsider until test completed "triple-blind" study = twofold visually impaired study in which individual translating results is likewise blinded (ex = analyst)

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What is sufficient verification? factual examinations searching for examples in your information in the wake of representing arbitrariness/vulnerability and utilizing this data to draw surmisings about procedure/populace being concentrated on are these outcomes a sufficiently major arrangement for me to mind? are these outcomes because of arbitrary possibility? are these outcomes generalizable?

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What is sufficient evidence? test size = # of perceptions (or bits of gathered information) that constitute an outcome ex = # of subjects per bunch in trial in case you\'re attempting to put forth a general expression around a populace, greater specimen size  more exact proclamation

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Controls! inner verification for your analysis negative control - demonstrates that a negative result is conceivable in your framework positive control - demonstrates that a positive result is conceivable in your framework "What else could have brought about watched impact?"

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Baking bread: a story of good controls

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Baking bread: a story of good controls does yeast Dani found in the back of the cooler still work? test outline controls

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Baking bread: a story of good controls negative control positive control demonstrates a negative result is conceivable demonstrates a positive result is conceivable

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Baking bread: a story of good controls negative result positive result

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Types of Data

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NOTE dat um = solitary a solitary estimation, result, and so forth dat a = plural a gathering of estimations, results, and so on.

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Types of Data quantitative information - numerical information size of estimation has size (a few things are greater than others) ex - tallness, cholesterol level subjective information - not numerical information, might be unmitigated or spellbinding size of estimation is an arrangement of unordered classes ex - sorts of trees, sorts of mixes

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Quantitative Data portrayed as far as numerical amount discrete information - there are just a limited # of qualities conceivable & values can\'t be subdivided and still important (ex - populace information) consistent information - information that can be measured on a continuum (physical estimations are for the most part this kind of information); can have any # esteem and be subdivided and still significant can be shown in outlines, tables, charts, histograms can be examined utilizing insights

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Qualitative Data depicted on premise of relative attributes shading shape surface temperature smell taste (for the most part not utilized as a part of exploration science) at times considered "less profitable" by examination researchers

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Example 1 Qualitative information - privateers convey parrots while ninjas don\'t.

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Example 1 Quantitative information - there are 6 privateers & 2 ninjas.

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Example 2 hot fudge sundae subjective information frosty to touch rich surface serving glass is dreary & straightforward quantitative information serving temperature is - 10 o C serving glass is 6 inches in stature cost $6.95

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Microscopy Data microscopists gather both subjective & quantitative information subjective information shade of example general structure of example state of cells kind of cells present & their area quantitative information how much greater is one example (or one particilar district of an example) versus another? what number of cells are in one a player in an example versus another?

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from Behonick, et al. (2007) PLoS One

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Data Collection precision = closeness of measured quality to a standard worth. exactness is autonomous of accuracy. ex - if in lab you acquire a weight estimation of 3.2 kg for a given substance, yet known weight is 10 kg, then your estimation is not exact (not near known worth) accuracy = the closeness of 2 or more estimations to each other. exactness is free of precision. ex = in the event that you measure 10 kg substance 5 times & get 3.2 kg every time, then your estimation is exceptionally exact however not precise.

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Accuracy versus Accuracy

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Properties of Light

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Light voyages @ 186,000 miles/sec ≈ 669,600,000 miles/hour can consider light stream of modest particles/vitality parcels ( photons ) a wave ( light waves ) we\'ll stay with this understanding

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The thing about waves … they\'re comprised of vitality , not make any difference at the shoreline at the laundromat

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<cue straightforward symphonious wave animation>

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Measuring Waves period (T) = time to one complete wave cycle recurrence (  ) = # periods per unit time; measured in Hz ex = # waves that pass a specific point in space amid particular time interim wavelength ( l ) = separation between same point on 2 successive waves (ie - 2 consecutive pinnacles, 2 successive troughs) adequacy (A) = greatest separation from most astounding purpose of top to harmony in 1 wave cycle A measure of time required to finish = T

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Frequency

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The thing about waves … they\'re comprised of vitality , not make any difference at the shoreline at the laundromat light waves ~ water waves however needn\'t bother with medium to travel through can move through medium or vacuum quickest in vacuum, moderate down in medium vitality in light waves = electrical & attractive fields  light = electromagnetic radiation

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1 m 10 6 nm 10 6 nm 10 –5 nm 1 nm 10 –3 nm 10 3 nm 10 3 m Micro-waves Radio waves Gamma beams X-beams UV Infrared Visible light 380 450 500 550 600 650 700 750 nm Shorter wavelength Longer wavelength Lower vitality Higher vitality EM Spectrum wavelengths 400 – 700 nm constitute unmistakable light for people higher recurrence lower recurrence

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EM Resources EM Wave Propagation Tutorial http://micro.magnet.fsu.edu/preliminary/java/electromagnetic/index.html Basic EM Wave Properties Tutorial http://micro.magnet.fsu.edu/groundwork/java/wavebasics/index.html

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transmitted reflected Properties of Light assimilated

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Microscopy Techniques target light source transmitted brilliant field stage DIC

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target light source Transmitted Light plentifulness object = pigmented or recolored sample ex = histology examples seen w/brightfield microscopy stage object ex = most natural specimens seen w/stage or DIC microscopy

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Objects and transmitted light wave sufficiency object seen as shading stage object not seen

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contrast = distinction in shading & light between parts of an article/picture requred to see an item by magnifying instrument can originate from varieties in power (DIC, stage) shading (splendid field, fluorescence)

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Contrast cells commonly are straightforward (not abundancy objects) stage protests low conversely differentiate producing systems transform stage contrasts into force contrasts so we can see unstained cells utilizing transmitted light ex = DIC microscopy .