IB Physics Inquiry Cube, Measurement, & Uncertainty

Welcome to STEM Physics!

Sit in desk of your choice.

I’m excited to work with you:

-making sense of our world

-developing science & math skills

- Design, build, and test engineering projects _______________________________________

Questions?

BRING First Day of Classes :

-pencil, spiral notebook, 3-ring binder ☺

Physics in the news:

Sunset Apollos

60 ^th Anniversary (est. 1959)

Physics in the

news:

Wildfires in the

Amazon

… and our

changing

climate

Breaking news…

Physics in the news:

Electric scooters hit Portland…

Helmets = yes

sidewalks = no…

Day 1: Welcome to STEM Physics

I’m glad you are here!

Sit in desk of your choice

Take out:

pencil

Put into backpack:

Cell phone and earphones,

Powered off

Distraction free (nice bun, though…)

Where do you come from?

Rachel Carson Middle Cedar Park

Meadow Park Stoller

Others? From other towns? Where?

We are ALL LINK Crew buddies for each other!

Introductions

Learn your partner’s:

- first and last name

- one thing they look forward to about this school yea

(remember it!)

Seating map

Course Outline

Need Parents Signature

Website tour

-Search google for “ STEM Physics schilling”

- Also see canvas STEM Physics site…

- “Beaverton student bookmarks”

- https://www.beaverton.k12.or.us/PS/Pages/Stu

dent-Bookmarks.aspx

Inquiry Cube ^{(pg 3 pkt)}

1. What qualities do scientists have? What are scientists like?

2. Draw what a scientist looks like.

3. How do Scientists do their work? How would

they describe a scientific investigation?

Front row: notice the blue circle on floor,

your desk will go back there after this…

Colored dot teams: front desks turn around to

point desks head to head with back desks

Inquiry Cube

4. What are questions we can investigate about this cube?

Do not touch, turn, lift, or

move the cube in any way.

Inquiry Cube

4. In your research team, determine:

What’s on the bottom of the cube?

Do not touch, turn, lift, or move the cube in any way.

(Answer with evidence-based

explanation)

What’s on the bottom of the cube?

(evidence-based explanation):

-Number sequence

-opposite sides add to …

(two different but related observations

create a stronger argument!)

Inquiry Cube

5. What is science?

(How is it different than asking your best friend or

looking something up on Wikipedia?)

Science is… (notice the red… but don’t write!)

Science originates in questions about the world.

Science is…

Science originates in questions about the world.

Science uses observations to construct explanations

(answers to the questions). The more observations you had that

support your proposed explanation, the stronger your explanation, even if

you could not absolutely confirm the answer by examining the bottom of the

cube.

Science is…

Science originates in questions about the world.

Science uses observations to construct explanations

(answers to the questions). The more observations you had that support your proposed explanation, the stronger your explanation, even if you could not absolutely confirm the answer by examining the bottom of the cube.

Scientist make their explanations public through

presentations at professional meetings and journals.

Science is…

Science originates in questions about the world.

Science uses observations to construct explanations

(answers to the questions). The more observations you had that support your proposed explanation, the stronger your explanation, even if you could not absolutely confirm the answer by examining the bottom of the cube.

Scientist make their explanations public through

presentations at professional meetings and journals.

Scientists present their explanations and critique the

explanations proposed by other scientists.

Science is…

Science originates in questions about the world.

Science uses observations to construct explanations

(answers to the questions). The more observations you had that support your proposed explanation, the stronger your explanation, even if you could not absolutely confirm the answer by examining the bottom of the cube.

Scientist make their explanations public through

presentations at professional meetings and journals.

and critique the explanations proposed by other

scientists.

Science is… finding and using patterns in nature to predict the

future or understand the past.

(Now write!)

Inquiry Cube #2

In your research groups for the second investigation:

Do not touch, turn, lift, or

move the cube in any way.

Inquiry Cube

6. First Hypothesis: (just guess) confidence:

7. Data

(pg 4 pkt):

8. Patterns: a. b. c.

(Research groups plan to publicly share your findings and evidence)

Low

Medium

High

Inquiry Cube

Research groups publicly share your findings and evidence.

9. What is the benefit to hearing other research groups’ ideas?

… gain further understanding! ☺

Inquiry Cube

Scientists use patterns in data to make

predictions and then design an experiment to assess the accuracy of their prediction. This process can also produce additional data.

10. Use your observations (data) to make a

prediction of the number in the upper-right

corner of the bottom.

Inquiry Cube

What is another test we could perform to

determine with even more confidence (less

error) what is on the bottom?

Inquiry Cube

With your limited funding you are able to purchase a small amount of technology and other equipment in order to test your prediction…

… mirror and probe: decide which corner to inspect, and why,

then inspect (only the corner!), and make

your final hypothesis.

Inquiry Cube

11. Final Hypothesis confidence:

Low

Medium

High

Inquiry Cube

Finally… YOU MAY LOOK AT THE BOTTOM!

Inquiry Cube

take 2 minutes to write…

*12. Describe how your confidence changed from first hypothesis to final hypothesis and why?

*13. How is this activity like real science?

*14. What about science doesn’t this activity

capture?

Checking in (pg 3 science is) :

Science originates in questions about the world.

Science uses observations to construct explanations

(answers to the questions). The more observations you had that support your proposed explanation, the stronger your explanation, even if you could not absolutely confirm the answer by examining the bottom of the cube.

Scientist make their explanations public through

presentations at professional meetings and journals.

and critique the explanations proposed by other

scientists.

End of inquiry cube

Student Questionnaire, and What’s Up With This?

Please be thoughtful.

Your HW: course outline (read/sign with home folks) Student Questionnaire

Finish Inquiry Cube (pg 3-4)

Day 2: take out: packet, spiral, calculator, signed paper, Student Questionnaire, highlighter, PLANNER

Agenda

Review Inquiry Cube

Whats up with this physics? (6 period)

Asking Good Questions Average & Uncertainty Accuracy & Precision

Due Tomorrow

Inquiry Skills & Data Sets Practice (pg 5 and 6)

Opening Question:

What makes for a good science question?

Due Today

First quiz: Thursday/Friday, Sept 6/7

Good Science Questions

✔ Can be answered with observable data.

✔ Leads to explanations about how the world works.

✔ Allow us to predict the future

or understand the past.

Debrief Inquiry Cube (?need to see cube?):

Discuss with teammates: pg 4, #12, 13, 14

(I’ll come stamp your work on pg 4…)

Inquiry Cube

10. Use your observations (data) to make a prediction of the number in the upper-right

corner of the bottom. (what pattern causes it to be an 8 , not 5 ? )

*12. Describe how your confidence changed from first hypothesis to final hypothesis and why?

*13. How is this activity like real science?

*14. What about science doesn’t this activity

capture?

Checking in (pg 3 science is) :

Science originates in questions about the world.

Science uses observations to construct explanations

(answers to the questions). The more observations you had that support your proposed explanation, the stronger your explanation, even if you could not absolutely confirm the answer by examining the bottom of the cube.

Scientist make their explanations public through

presentations at professional meetings and journals.

and critique the explanations proposed by other

scientists.

Turn in safety signature sheet to alphabet stick

Birthday list, Pet peeves, and expectations, drug

consequences, groundrule #1

Good Science Questions (put into class notes spiral)

✔ Can be answered with observable data.

✔ Leads to explanations about how the world works.

✔ Allow us to predict the future

or understand the past.

Which are “good science questions”?

1. Is there an end to the universe?

2. How does the thickness of a rope affect

the maximum tension it can withstand before

breaking?

From Questions to Making Measurements

& Collecting Data

Once you have a focused science question you need to know how to make measurements and collect data to inform yourself about how nature works.

1. You need an independent variable (manipulated variable): the one you change.

2. Then a dependent variable: the one you think will change as a result of the independent variable.

3. Then control as best as possible all other things that

might change the dependent variable.

Experimental Basics

Independent Variable: We change it

Dependent Variable: is changed by Independent variable

Controlled Variables: everything else that may effect the experiment

Practice: You observe that when you drop you textbook it makes a

loud sound on impact with the floor.

Example

You notice a book dropped from different heights creates a sound of different intensity. So you ask “How does the height of the book affect the intensity of sound when it hits the ground?”.

The independent variable

The dependent variable

: ____________

What are the controlled variables:

(5 minutes)… take out highlighter…

Classwork on page 5

#1-18

Review pg 5…

"How does the breaking strength a column of cement depend on its diameter?"

10. What is the independent variable__________

11. What is the dependent variable? __________

12. What are the controlled variables? (i.e. what

must you keep constant?)

Break… turn in student questionnaire

Who is Schilling?

Get your calculator out…

Wild guess: How tall am I?

How certain are you of that estimate?

All measurements have some degree of UNCERTAINTY:

6 ft +- .5 ft

Which has more UNCERTAINTY:

6 +- 1 ft Or 6.000 +- .005 ft

Larger

uncertainty

More “precise”

Less uncertainty

Our goal when making measurements:

Good PRECISION and good ACCURACY

PRECISION: make detailed measurements

6.05 ft is more precise than 6 ft

using finely-calibrated tools

ACCURACY: how close to the true value a measurement is

6 ft is more accurate for my height than 12.335 ft (I’m 5.95 ft tall ☺ )

using calibrated tools

Data: range and uncertainty

What is the same about these data sets?

What is different about these data sets?

Set A: 19, 15, 17 = length of a shoe

Set B: 17, 23, 11 = length of same shoe Which sets seems better? Why?

How can we visually communicate this?

Data

Your Science is only as Good as your Data

Summarize these 2 data sets? How do we

communicate one seems better than the other.

Set A: 19, 15, 17 Set B: 17, 23, 11

Average 17

17

Uncertainty in Average =

Range 2

Average Uncertainty 17 +- 2

17 +- 6

Put in toolbox

Data

Your Science is only as Good as your Data

Summarize this data set? How do we

communicate one seems better than the other.

Set C: 20, 20, 17

Average Uncertainty 19 +/- 2

Uncertainty in Average =

Range 2

Range = biggest number – smallest number

Put in toolbox

General Rule: uncertainty has only 1 significant figure

Science is Data Driven

Your Science is only as Good as your Data

Summarize these 2 data sets? How do we

communicate one seems better than the other.

Set D: 4.5, 4.6, 4.4 Set E: 112,121,117

Average Uncertainty 4.5 +/- 0.1

116.6666 +/- 5

Uncertainty in Average =

Range 2

Put in toolbox

Something weird here?

1.5

Science is Data Driven

Your Science is only as Good as your Data

Important practice:

Set F: 6, 8, 9

Average Uncertainty 7.6666 +/-

General Rule: uncertainty has only 1 significant figure Put in toolbox

8 2

So we have a 5-step process:

1- Find the math Average 2- Find the range

3- Find the rough uncertainty, by dividing the range by 2 4- Round rough uncertainty to 1 significant figure

5. Match the decimal place of average to that of the uncertainty

Range = 9 - 6 = 3

Set G: 423,487,461

Try it yourself with 5-step process:

1- Find the math Average 2- Find the range

3- Find the rough uncertainty, by dividing the range by 2 4- Round rough uncertainty to 1 significant figure

5. Match the decimal place of average to that of the uncertainty

32 Average Uncertainty 457 460 +/- 30

Range = 487-423 = 64

(worktime)… Classwork on page 6

#1-8

stopped here

Day 3: take out: planner , ^packet

spiral, calculator, student ID

Agenda

Average & Uncertainty Accuracy vs Precision Measurement Activity

Due Today

Inquiry Skills & data sets (pg 5-6) Upcoming Events

quiz next class: review pg 3, 5, 6, 7, 8, 9 packet, and classnotes

Opening Question:

What is the Average and Uncertainty of:

1001, 3001, 2001 10, 11, 15

45, 75, 50

… and discuss stumpers from p 6 of packet

Due Tomorrow

Take textbook home, on pages 1-7, read all red headings, bold faced phrases, highlighted words, and cartoons (no more

Opening Question:

What is the Average and Uncertainty of:

1001, 3001, 2001 (2000 +-1000)

10, 11, 15 (12 +-3)

45, 75, 50 (60+-20)

Science is Data Driven

Your Science is only as Good as your Data

Summarize these 2 data sets? How do we

communicate one seems better than the other.

Set D: 4.5, 4.6, 4.4 Set E: 112,121,117

Average Uncertainty 4.5 +/- 0.1

116.6666 +/- 5

Uncertainty in Average =

Range 2

Put in toolbox

Something weird here?

1.5

Science is Data Driven

Your Science is only as Good as your Data

Important practice:

Set F: 6, 8, 9

Average Uncertainty 7.6666 +/-

General Rule: uncertainty has only 1 significant figure Put in toolbox

8 2

So we have a 5-step process:

1- Find the math Average 2- Find the range

3- Find the rough uncertainty, by dividing the range by 2 4- Round rough uncertainty to 1 significant figure

5. Match the decimal place of average to that of the uncertainty

Range = 9 - 6 = 3

Set G: 423,487,461

Try it yourself with 5-step process:

1- Find the math Average 2- Find the range

3- Find the rough uncertainty, by dividing the range by 2 4- Round rough uncertainty to 1 significant figure

5. Match the decimal place of average to that of the uncertainty

32 Average Uncertainty 457 460 +/- 30

Range = 487-423 = 64

Uncertainty of a data set:

Uncertainty is =

has 1 Significant Figure

: represents possible mismeasurement, so we tell people how far off we may be.

Review from last class:

Review HW packet

Page 5 and 6 Questions

-Get textbook -Groundrule #2

-physics buddies assignment

Our goal when making measurements:

Make detailed measurements (good ^PRECISION )

with well-calibrated tools (good ACCURACY )

Uncertainty in a measuring tool

is at least as big as a half increment, and possibly much bigger due to your technique ☺

Each increment = .1cm

So uncertainty is

½ of .1cm,

or +- .05 cm

Measuring tools:

How many trials and digits?

Trials Digits 1. our standard rulers

2. our standard meter sticks 3. our stopwatches

4. electronic mass scales

5. large graduated cylinders

How many trials and digits?

Trials Digits 1. our standard rulers

2. our standard meter sticks 3. our stopwatches

4. Electonic mass scales, 0.1g 5. large graduated cylinders

Measuring tools:

3 3 3 1

3 ??? You

0.1 g

Human reaction time

½ of

1mm

Uncertainty (aka: “error”) (60+-20)

– Uncertainty is 1 Significant Figure

Uncertainty in a measuring tool is generally a half

increment.

Uncertainty is =

represents possible mismeasurement, so we tell people how far off we may be.

Review

Measurements activity, pg 7-8

Make your measurements with

ACCURACY and PRECISION!

measurement activity pg 7

Pg 8

Quiz Topics

( review pg 3, 5, 6, 7, 8, 9 packet, and classnotes )

• What is science? (pg 3 of packet)

• Characteristics of good scientific questions

• IV and DV’s: identify which is which

• Calculate:

average, range, uncertainty

• Measurements:

accuracy vs. precision

Day 4: take out: packet(pg 8), calculator

Agenda

-new seat next class

-

-Review pg 7, 8 -Quiz #1

-Graphs, & Logger Pro intro

Due Today

pg 7-9 of packet Upcoming Events

First Lab:

Opening Question:

What is this measurement? ?? +- ??

Due Tomorrow

53.0+-.5 ml

measurement activity pg 7

#1’s: turn on computer and monitor at your lab station,

and login with your username and

password (ID# and your personal pw)

(at least 1 uppercase)

(same as chromebook)

Review pkt pg 7&8…

Use elmo,

+- ???

Review pkt pg 8…

+- ???

8.8 g

90.5 g

.047 g

Continue update here…

+-.005

3.3+-.3 +- 3

+- 50

Quiz 1:

Patterns (15 minutes, can use calculator)

CELL PHONES

&

“SMART” WATCHES IN BACKPACK

(SIT SILENTLY UNTIL ALL ARE DONE…)

Graphs:

show relationships and patterns

Graphs:

show relationships and patterns

Time of growth

What’s different?

What’s

similar?

a computerized tool that

CREATES GRAPHS, AND HELPS US LOOK FOR

PATTERNS

AMONGST VARIABLES

Logger Pro

(pg 10)

Scenario A:

Plot the following data set collected from a car traveling at a constant speed of 5 m/s. Use the Vernier software and find the best-fit line

Time in seconds (Independent) Distance in meters (Dependent)

0.0 0.0

1.0 5.0

2.0 10.0

3.0 15.0

4.0 20.0

5.0 25.0

1. Best-fit for this graph:

2. Extrapolate – Tell what distance you would get

according to your line if the time were 10.0 seconds.

Watch this! Using Logger Pro

(pg 10)

Do NOT save file at end, instead… power down program, computer and monitor…

Scenario A:

1’s: computer operator 2’s: read data to 1’s

3’s/4’s: make sure data entry to computer is

correct

… Show me each graph

before you move on to next

Make sure that the best fit line is clearly visible on your graph as well as the equation for the best fit line.

“you’ll likely finish scenario A and B today”

Scenario

#A Plot the following data set collected from a car traveling at a constant speed of 5 m/s. Use the Vernier software and find the best-fit line

Time in seconds (Independent) Distance in meters (Dependent)

0.0 0.0

1.0 5.0

2.0 10.0

3.0 15.0

4.0 20.0

5.0 25.0

1. best-fit line:

2. Extrapolate your graph to 16 seconds (analyze, interpolate)

3.Use equation…– Tell what value you would get using

Now go to your computer, and do scenario A

Using Logger Pro

(pg 10)

Scenario B:

Adding error bars:

double-click column heading options

error bars

fixed value

Point out: set B and C to zero…

End day 4…

… new seats next class!

Day 5: take out: packet(pg10), calculator

Agenda

New seats! Introduce yourself!

Quiz makeups A/T

Finish scenario B, logger pro pg 10 with uncertainty bars

Lab: Rolling ball on flat ground (design, data collection, logger pro)

Due Today

scenarios A and B of pg. 10 Upcoming Events

4 experiments

Opening Question:

Wild guess: How far will this steel ball roll after 6 seconds?

Due Tomorrow

graph and eqn for your data from today’s lab, pg 12

Review pg 10:

1, 2, 3

Scenario A (linear):

Scenario B:

Adding error bars:

double-click column heading options

error bars

fixed value Adding title:

double-click graph

Answer 5-8 carefully!

What’s -1.219E-017 mean?

And

Adding error (uncertainty)bars, and Title:

double-click column heading options

error bars

fixed value

Scenario B:

-1.219 X 10

-.00000000000000001219

Quick review: scenario B… use elmo

PG 11:

Ball on Flat Ground Lab

By the End of this Experiment You Should…

Understand the patterns of motion for a low friction rolling ball.

Be able to express those patterns graphically, mathematically, visually, and with words.

Language Objective

Content Objective

Ball on Flat Ground Lab

Wild Guess:

How far will this steel ball roll after 6 seconds?

(Observation – show ball off of 6-book ramp for 1 second)

Research Question:

How does the time a ball rolls affect the distance

it will roll?

Ball on Flat Ground Lab

Hypothesis:

1) sketch in graph form (think about one set-up

previous slide

then think doubling or halving the time)

2) in words “I think the distance rolled depends on the time rolled in a ______ relationship”

distance

time

Share your hypothesis with teammates,

explain your reasoning ☺

Ball on Flat Ground Lab

Variables:

independent variable (IV):

dependent variable (DV):

controlled variables:

6 books

6-7 people per group

1.00 m 2.00 m 3.00 m 4.00 m

Distance Rolled (m)

+/- 0.05

Time (s) +/- 0.2 t _avg

(s) +/- 0.2

Trial 1 Trial 2 Trial 3

0.00 1.00 2.00 3.00

Ball on Flat Ground Lab You make the Data Table

Value of controlled variables: Y

axis

X

axis

Ball on Flat Ground Lab

5 Groups QUIETLY in hallway, each with own eqpt.

1 roller (& ramp carrier) 4 timers (& book carriers) 1 ball stopper

1 Data entry into notebook Collect 3 CONSISTENT

trials of times to nearest

hundreth… 0.63 s not 0.6 s

Back in classroom:

1. Everyone write down time data into table 2. all calculate Average time

3. data entry into Logger Pro, error bars

identify the pattern… equation and graph…

does it make sense?

…stay with your teams, focus on your work!

save here!

Graphing the ball Data:

1. We will use Logger Pro

2. Set-up columns (name, unit) for time, distance

1. Add fixed error values for uncertainty to each column

3. Enter data in each column

4. Graph Options (Add title, check point protectors, uncheck connect points)

5. Find simplest best-fit line… then draw it (with its

equation) onto pg 12

Stop day 5

Due Tomorrow

Pg 11: finish all details and

pg 12: graph and eqn for your data from

today’s lab, of packet

Update, using ball lab instead of spring

Good Example of a Whiteboard

Distance ball rolled (m)

Distance = ____ * time

Height =

Summary:

Using Logger Pro (by Vernier)

(Page 10)

We can create graphs,

with error bars representing uncertainty of measurements, and use the graph

and/or

equation of the best-fit line

to PREDICT the future!!!

Using Logger Pro (by Vernier)

(Page 10)

You can download Logger Pro at home for free…

see class website for instructions

https://www.beaverton.k12.or.us/PS/Pages/LoggerPro.aspx

Stop here day 5

Agenda:

See old quiz (next class)

Data analysis toolbox Making Sense of the Ball Experiment

logger pro whiteboards

-present your findings conclusion writing

Due Today

Data/graph/equation for Ball Experiment

Due Tomorrow

pg 12, and pg 13: 1 thru 4

Opening Question:

Below is a graph of gas used in a car and how far the car was able to travel. What type of relationship is there between gas and distance traveled?

Day 6: take out: packet(pg 12), calculator

What type of relationship is there between

gas and distance traveled?

Opening Question

Below is a graph of gas used in a car and how far the car was able to travel.

What type of relationship is there between gas and distance traveled?

What does the slope tell us? What does the y-intercept tell us?

How would this change for a Prius?

What could explain the intercept?

See quiz 1 4= highly proficient (14 -16) 3= proficient (12-13.5)

2= nearly proficient(8 -11.5)

1= developing(below 8)

Pickup Data Analysis Toolbox Logger pro your data (3 of you) Create Whiteboard (3 of you)

to present your findings

…see tips below…

Graphing the ball Data:

1. We will use Logger Pro

2. Set-up columns (name, unit) for time, distance

1. Add fixed error values for uncertainty to each column

3. Enter data in each column

4. Graph Options (Add title, check point protectors, uncheck connect points)

5. Find simplest best-fit line… then draw it (with its equation) onto pg 12,

and make distance prediction when time= 6 s

Ball on Flat Ground Experiment

WHITEBOARDS:

Presenting your findings:

Lets do 5 things…

Presenting our findings:

1. This is Science – we need Data, some

information on experimental set-up, and a concluding pattern.

2. With multiple groups we also need to help each other easily compare the data.

3. What form of data is easily and quickly compared?

4. What must we insure about every groups’

graphs to make them easily and quickly comparable?

5. Make beautiful graphs and place up front

…graphs! ☺

…same scales on axises! ☺

Good Example of a Whiteboard

Distance ball rolled (m)

Distance = ____ * time

Book Height = IV =

DV=

Teammates names=

Predicted distance for 6 seconds of time=

Specific title:

… and make prediction for 6 seconds’ roll distance

(graphically, and using the equation)

… what is your

confidence in your

prediction?

Send up one teammate to get whiteboard and

marker…

Prepare for Board Meeting

Discuss with your team:

- what does each axis represent?

- what pattern do you notice in the data… if you double the time, what happens to the

distance?

-what does the y-intercept mean about the data?

-what does the slope of the line mean?

Board Meeting

Then erase your board…

Conclusion (write all of this, neatly, pg 12!)

Since all my data fits on a single best-fit line, I conclude that there is a linear relationship between the roll distance and the amount of time the ball rolls .

This can be modeled mathematically as

So I predict with _____ confidence based on our class data that for a 6 second roll, the ball will roll _____ m because the best-fit line hits near the center of most of the data points and the

prediction is _________ our data range.

roll distance= .??? m/s X time of roll

Test Prediction…

Half of you stand at your wild guess…

Half stand at data-based prediction…(with timers)

Test Prediction…

I get what Mr. Schilling means when he says “we take some measurements about the motion of a rolling ball, apply some mathematics to find a

pattern, and then predict the future position of a

ball.”

Would our model work for predicting

out to 30 seconds?

… not if friction slows the ball down…

How could 2 different groups, both doing a good

job, get different graphs?

Test Prediction

I get what Mr. Schilling means when he says

“we take some measurements, apply some

mathematics to find a pattern, and than predict the future.”

But with friction it is more complicated and our

mathematical model starts

to break down...

Test Evidence-based Prediction

Science works!

We can find a pattern in nature and use it to accurately predict the future.

Wild guess sometimes close, sometimes not.

How do you know which of these it is? With careful investigation we can predict the future again and again – with some level of

confidence.

BallExperiment

Reasoning & Making Sense of the Data

1. What does the slope tell us about a ball?

a) What are the units of the slope?

2. Why do all of them have a zero intercept?

Making Sense of the Slope

did each team get the same slopes?

Agenda

- See canvas, Quiz 1

-test prediction, confidence level -Notes: Linear Pattern -Lab 2: ball on

ramp

Due Today: pg 13: 1-4

Due Tomorrow

download logger pro at home (see canvas),

Opening Question:

What does the slope of the distance vs. time graph

represent?

Day 7: take out: I stamp packet(pg 13), calculator, spiral, timer

speed

See quiz 1 4= highly proficient (14 -16) 3= proficient (12-13.5)

2= nearly proficient(8 -11.5)

1= developing(below 8)

Conclusion (write all of this, neatly, pg 12!)

Since all my data fits on a single best-fit line, I conclude that there is a linear relationship between the roll distance and the amount of time the ball rolls .

This can be modeled mathematically as

So I predict with _____ confidence based on our class data that for a 6 second roll, the ball will roll _____ m because the best-fit line hits near the center of most of the data points and the

prediction is _________ our data range.

roll distance= .??? m/s X time of roll

Test Prediction

Half of you stand at your wild guess … Half stand at data-based prediction…

with timers! ☺

“we take some measurements, apply some

mathematics to find a pattern, and then predict

the future.”

Test Prediction

I get what Mr. Schilling means when he says

“we take some measurements, apply some

mathematics to find a pattern, and then predict

the future.”

Would our model work for predicting

out to 30 seconds?

… not if friction slows the ball down…

Test Evidence-based Prediction

Science works!

We can find a pattern in nature and use it to accurately predict the future.

Wild guess sometimes close, sometimes not.

How do you know which of these it is? With careful investigation we can predict the future again and again – with some level of

confidence.

Ball Experiment

Research Extension Question: (now that you

have some experience and knowledge with

rolling balls, what further high school level

question could you investigate?)

Classnotes in spiral ☺

Pattern: Linear

Pattern: Linear

When t is doubled, the distance will double.

d

t

Slope = Speed, Velocity

d = vt

Distance vs Time

for a Constant Velocity

(The bigger the

slope, the faster the speed)

so when x x , y y

and when x x , y y

Pattern: Horizontal Line

v doesn’t change, so v = v

v

t

v = v

Velocity vs Time Constant Velocity

(As the ball rolls along

the floor, the speed stays

the same)

review

pg 13, parts 1 through 4

… and then,

on to our

next experiment! ☺

In spiral, clean sheet of notebook paper, using

same format as ball on flat ground lab

Ball on Ramp Lab

(clean binder paper in spiral)

Wild Guess: How much time will it take a ball

bearing to roll 2.50 m down ramp with 6 books under?

Research Question:

How does the time a ball has rolled affect the

Ball on Ramp Lab

Hypothesis:

1) sketch in graph form

2) in words “I think when ball rolls down ramp, the distance depends on the time fallen in a ______

relationship”

distance

time

Ball on Ramp Lab

Variables:

1. IV: identify the independent variable

2. DV: identify the dependent variable

3. Controlled variables:

Ball on Ramp Lab

Method:

1. Experimental set-up

2. How will you change the independent variables

3. How will you control the controlled variables

Ball on Ramp Lab–

You make the Data Table

Value of controlled variables: Distance Rolled on

ramp (m) +/- 0.1

Time (s) +/- 0.2

Average Time (s) +/- 0.2

Trial 1 Trial 2 Trial 3 0.0

0.75 1.50 2.25 3.0

Y axis

X

axis

Ball on Ramp Lab

same Groups QUIETLY in hallway, 6 book ramp height

1 roller & data entry into notebook 4 timers (& book/ramp carriers)

1 ball stopper 1 data recorder

Collect 3 CONSISTENT trials of times… “3, 2, 1, start!” SMOOTH,

STRAIGHT ROLL in ramp

Share data for all teammates, calculate average times

then Enter data into Logger pro and

save to

public folder

Next class:

Share data for all teammates, calculate average times

HW: download logger pro at home (from class website) and

Do pg 13: 5 and 6

Agenda

logger pro graphing of lab , white boards, write

conclusion, test prediction -Quadratic Pattern notes -Physics Buddies

Due Tomorrow

Ball on Ramp Lab Report, and

Opening Question:

If you were absent from a day of this class, what would you need to find out, and who would you call?

Day 8: take out: Data analysis toolbox, Ball On Ramp lab in spiral, calculator

Coming up: Quiz #2 on Linear and Quadratic

Patterns, mon/tues Sept

24,25

Share data for all teammates, calculate average times

then Enter data into Logger pro

Ball on Ramp Lab

2 data entry into Logger Pro

Use same time scale (5s) and distance scale (5 m)

and (B and C = 0)

2 white board your results

2 identify the pattern… does it make sense, and make your prediction

… stay with your team,

focus on your work!

Linear, or something

… and make

prediction for time to reach 2.5 m on ramp (graphically, and using the

equation)

… what is your

confidence in your

prediction?

Ball on Ramp Lab–

You make the Data Table

Value of controlled variables: Distance Rolled on

ramp (m) +/- 0.1

Time (s) +/- 0.2

Average Time (s) +/- 0.2

Trial 1 Trial 2 Trial 3

0.0 0 0 0 0

0.75 .7 .8 .8 .77

1.50 1.0 1.1 1.1 1.06

2.25 1.4 1.4 1.5 1.42

3.00 1.6 1.7 1.7 1.63

Y axis

X

axis

Good Example of a Whiteboard teammates names specific title

Time ball rolled for Distance ball rolled (m)

Distance = ____ * equation

6 book ramp

Predicted time

to roll 2.5 m =

Go to logger pro ☺… keep your file open!!!

… then board meeting…

… then back to logger pro…

Good Example of a Whiteboard

Ball rolling down ramp

Time ball rolled for Distance ball rolled (m)

Distance = ____ * (time) ²

6 book ramp

Predicted time

to roll 2.5 m =

Ball on Ramp Lab

(draw this in your own lab report )

Notice, what’s the speed of the ball doing as it moves down the ramp?

accelerating!

Ball on Ramp Experiment

Conclusion:

Since all of my data fits on a single best-fit line that is ________, I conclude there is a ________

relationship between the distance a ball rolls on a

ramp and the time it is allowed to roll.

Ball on Ramp Experiment

Conclusion:

Since all of my data fits on a single best-fit line

that is quadratic, I conclude there is a quadratic

relationship between the distance a ball rolls on a

ramp and the time it is allowed to roll.

Ball on Ramp Experiment

Conclusion:

Since all of my data fits on a single best-fit line

that is quadratic, I conclude there is a quadratic

relationship between the distance a ball rolls on a

ramp and the time it is allowed to roll. This can be

modeled mathematically as:

Ball on Ramp Experiment

Conclusion:

Since all of my data fits on a single best-fit line that is quadratic, I conclude there is a quadratic relationship between the distance a ball rolls on a ramp and the time it is allowed to roll. This can be modeled mathematically as:

distance = ______ * time ² .

Ball on Ramp Experiment

Conclusion:

Since all of my data fits on a single best-fit line that is quadratic, I conclude there is a quadratic relationship between the distance a ball rolls on a ramp and the time it is allowed to roll. This can be modeled mathematically as:

distance = ______ * time ² .

Therefore I predict with ____ confidence based

on my data that it will take a ball _____ seconds

to roll down a 2.5m long ramp,