Be safe and always assume the barrel is loaded. Use a C clamp to fasten the launcher to the end of the table as shown below. Aiming is achieved by loosening the thumb screw and rotating the launcher to the desired angle above or below the horizontal as indicated by the plumb bob and protractor on the side of the launcher.
When the angle has been selected, gently tighten the thumb screw. Do not over tighten or damage may occur to the ridges on the extruded barrel. The purpose of this experiment is to determine the muzzle velocity of the launcher and to test the validity of the parametric equations governing projectile motion. Position and clamp the launcher to one end of the table, and adjust so that the ball will travel over the surface of the table and land on the tabletop.
Assume that the ball lands at the same level as it is launched and make sure that the launcher is arranged for this to happen. See instructions for aiming given above. Record the angle. Loading the ball: Always cock the launcher with the ball already in the piston. Place the ball in the barrel. Push the ball down the barrel with the pushrod until the trigger catches the piston. One audible click indicates that the piston is cocked in the shortest range setting, two clicks indicate the medium range and three clicks set the piston in the long range position.
For this experiment use the long range position. Fire one shot to locate where the ball hits the table. When the ball hits the paper it will leave a mark or indentation. Fire several shots, being careful not to change the aim of the launcher. Measure the horizontal distance from the bottom of the ball as it leaves the barrel this position is marked on the side of the barrel to the point of impact. Record this distance — the horizontal distance or range traveled by the ball.
Find the mean of the range values. Record this information and proceed to calculate the initial speed or muzzle speed of the ball using the mean of the range and the angle of the launch. Show all work in the space provided. Now use the initial velocity to calculate the maximum height attained by the ball in its flight.
Record this calculated theoretical value. Again show work.
No document with DOI "10.1.1.409.5001"
Launch the ball and observe its motion hopefully through the hoop. If it does not go through the hoop adjust the position until it does so. Use the hoop as a means to judge the actual maximum height of the ball. Record this observed value. Choose a convenient angle for launching. Measure the vertical distance from the bottom of the ball as it leaves the barrel this position is marked on the side of the barrel to the floor.
Record this distance — the vertical component of displacement between launch and impact.
Use the mean value of the muzzle speed found in part A along with the angle of the launcher and the vertical displacement to calculate a predicted range and time in the air. Also, use a stopwatch to measure the time in the air. Repeat several times to get an average value for each.This theorem states that when the speed of liquid flow increases, then the pressure in the liquid will be decreased based on the energy conservation law.
From the energy conservation principle, this theorem can be derived. So the fluid with less speed will use more force compare with a fluid that is flowing very fast. The formula of this theorem can be given as:. Consider a slight viscosity liquid flowing with laminar flow, then the whole potential, kinetic, and pressure energy will be constant.
Whenever two boats are moving side by side in a similar direction, then the air or water will be there in between that moves quicker compare with when the boats are on the remote sides. Therefore because of the change in pressure, the boats are pulled in the direction of each other due to attraction. The wings of the plane have a specific shape. When the plane moves, the air flows over it with a high speed as contrasted with its low surface wig. So this principle creates a change in pressure because of the flow of air on the up surface of the wing.
If the force is high than the mass of the plane, then the plane will rise. In these, due to the motion of the piston within a cylinder, high speed of air can be supplied on a tube that is dipped in the fluid to spray. The air with high speed can create less pressure on the tube because of the rise in the fluid.
What is a Bernoulli’s Theorem : Derivation & Its Limitations
The trouble in the atmosphere due to rain, hail, snow, the roofs of huts will blow off without any harm to another part of the hut. The blowing wind forms a low weight on the roof.
The force under the roof is bigger than low pressure because of the difference in pressure; the roof can be raised and blown off through the wind. In this burner, the nozzle generates gas through high velocity. Because of this, the force within the stem of the burner will decrease. Thus, air from the environment runs into the burner.
Once a rotating ball is thrown, then it moves away from its normal path within the flight.To get the best possible experience using our website, we recommend that you upgrade to latest version of this browser or install another web browser. Network with colleagues and access the latest research in your field. Now offered virtually. Chemistry at Home Explore chemistry education resources by topic that support distance learning.
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Funding Funding to support the advancement of the chemical sciences through research projects. Virtual Chemistry and Simulations. Several new simulations are added each year. Every simulation is open for teachers and students to access. Users can copy any of the Google Forms to their Google Drive to edit and use. Search by subject and grade level. Mixed Reception This ChemCollective activity could be described as a murder mystery for chemistry students.
Aspirin Screen Experiment Explore the chemistry of aspirin virtually with four levels of experiments, including synthesis, thin layer chromatography, and reaction conditions. CK—12 Chemistry Simulations Nearly two dozen simulations cover topics like average atomic mass, solubility with rock candy, and freezing point depression with road salt. Titration Screen Experiment Give students titration practice virtually. It also has tools for teachers and students to create their own.
Blauch of Davidson College presents several interactive experiment simulations on topics such as equilibrium, kinetics, crystal structure, phase changes, gases, and more.I absolutely loved the tea tox. It tastes so good. I am sure the next month will help me continue my goals. Its really helps with bloating and digestion. Look at my new tummy. I didn't change much of my normal routine either while doing this.
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Indianapolis ranks near the bottom of the league in most pass defense categories. Jabaal Sheard gives the Colts a solid pass rush off the edge, and Johnathan Hankins is a rock in the middle of their defensive line. If the Bills' best bet to move the football is through the air. The game will be broadcast on CBS beginning at 1 p. You can follow along on Twitter with the following handles. Sean McDermott said the decision on whether Tyrod Taylor or Nathan Peterman will play quarterback with be made on Sunday with Taylor nursing an injury.
But the Colts seemed confident this week that Taylor would be the guy. We fully anticipate him playing. And if he doesn't, we know the kid has arm talent and he can spin it and throw it with the best of them.
We'll have to be at our very, very best no matter who plays. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of Advance Media New York. Colts: Preview, odds, prediction for Week 17Orchard Park, N. Tyrod Taylor, Jabaal Sheard While the Colts' front seven is a decent unit, their secondary is among the worst in the NFL.
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Please bookmark those pages to access comics in the future. A few of these services offer email newsletters so you can have the comics delivered to you, or you can follow them on Facebook.The map was so detailed we rarely needed anything else.
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We loved the welcome package--the map was so helpful with all of the highlighting of where we'd be staying, what route we'd take, and the sites we could see along the way. We used that map in conjunction with the book we received, the itinerary and just one book that we brought along with us.
We were able to see so many wonderful and beautiful things (things which weren't even on the itinerary--but that we just happened to pass by). We stopped by a town called Olafsvik for lunch one day and absolutely fell in love with its charm. Same with Husavik--loved that town.
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By subtracting the first score from the second for each subject and then analyzing only those "pure (paired) differences," we will exclude the entire part of the variation in our data set that results from unequal base levels of individual subjects. This is precisely what is being done in the t-test for dependent samples, and, as compared to the t-test for independent samples, it always produces "better" results (i.
If these assumptions are clearly not met, then one of the nonparametric alternative tests should be used. Technically, we can apply the t-test for dependent samples to any two variables in our data set. However, applying this test will make very little sense if the values of the two variables in the data set are not logically and methodologically comparable.
Following, is an example of a data set that can be analyzed using the t-test for dependent samples. WCC before WCC after case 1 case 2 case 3 case 4 case 5. However, the t-test for dependent samples analysis is performed only on the paired differences"ignoring" the raw scores and their potential differentiation.
Thus, the size of this particular difference of 1 will be compared not to the differentiation of raw scores but to the differentiation of the individual difference scores, which is relatively small: 0. Compared to that variability, the difference of 1 is extremely large and can yield a highly significant t value.
If there are more than two "correlated samples" (e. The repeated measures ANOVA can be considered a generalization of the t-test for dependent samples and it offers various features that increase the overall sensitivity of the analysis.
The breakdowns analysis calculates descriptive statistics and correlations for dependent variables in each of a number of groups defined by one or more grouping (independent) variables. In the following example data set (spreadsheet), the dependent variable WCC (White Cell Count) can be broken down by 2 independent variables: Gender (values: males and females), and Height (values: tall and short). GENDER HEIGHT WCC case 1 case 2 case 3 case 4 case 5. The resulting breakdowns might look as follows (we are assuming that Gender was specified as the first independent variable, and Height as the second).
For example, in the above example, you see the means for "all males" and "all females" but you do not see the means for "all tall subjects" and "all short subjects" which would have been produced had you specified independent variable Height as the first grouping variable rather than the second.
Statistical Tests in Breakdowns. If you are interested in differences concerning the means, then the appropriate test is the breakdowns one-way ANOVA (F test). If you are interested in variation differences, then you should test for homogeneity of variances. Other Related Data Analysis Techniques. Although for exploratory data analysis, breakdowns can use more than one independent variable, the statistical procedures in breakdowns assume the existence of a single grouping factor (even if, in fact, the breakdown results from a combination of a number of grouping variables).
Thus, those statistics do not reveal or even take into account any possible interactions between grouping variables in the design. For example, there could be differences between the influence of one independent variable on the dependent variable at different levels of another independent variable (e. You can explore such effects by examining breakdowns "visually," using different orders of independent variables, but the magnitude or significance of such effects cannot be estimated by the breakdown statistics.
Post-Hoc Comparisons of Means. Usually, after obtaining a statistically significant F test from the ANOVA, one wants to know which of the means contributed to the effect (i. One could of course perform a series of simple t-tests to compare all possible pairs of means. However, such a procedure would capitalize on chance.
This means that the reported probability levels would actually overestimate the statistical significance of mean differences. Without going into too much detail, suppose you took 20 samples of 10 random numbers each, and computed 20 means. Then, take the group (sample) with the highest mean and compare it with that of the lowest mean. The t-test for independent samples will test whether or not those two means are significantly different from each other, provided they were the only two samples taken.
Post-hoc comparison techniques on the other hand specifically take into account the fact that more than two samples were taken. Technically, it determines a linear combination of the dependent variables that best predicts the group membership. Another related type of analysis that cannot be directly performed with breakdowns is comparisons of frequencies of cases (n's) between groups. Specifically, often the n's in individual cells are not equal because the assignment of subjects to those groups typically results not from an experimenter's manipulation, but from subjects' pre-existing dispositions.
If, in spite of the random selection of the entire sample, the n's are unequal, then it may suggest that the independent variables are related. For example, crosstabulating levels of independent variables Age and Education most likely would not create groups of equal n, because education is distributed differently in different age groups.