BSC201 JASP Instructions PDF

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Jasp Instructions Research Randomiser: https://www.randomizer.org/ Left Hand 1 Right Hand 2

Howmanys et sofnumber sdoy ouwantt ogener at e ? 1 (classroom), if you chose 3 classrooms there would be 3

Howmanynumber sperset ? Sampl eSi z e Numberr ange( e. g. ,150)Fr om:1To:2 Numberofl ev el samongI V,I nt hi ss ampl et her ei s2l ev el s( handednes s ) , l ef thandr i ghthand. Doy ouwi sheac hnumberi nas ett or emai nuni que ?No Doy ouwi sht os or tt henumber st hatar egener at ed?No( Random As s i gnment ) Howdoy ouwi s ht ov i ewy ourr andom number s ?Upt oYou( NoPl ac e Mar k er )

Create Random Order Sheet:

For this experiment we have to do pseudo random assignment. Last name A-L = 1 (Left hand). M-Z = 2 (Right Hand). Open Excel 1 column IV, 1 column DV hand taps Collect data by first name: in chat 1 of 2 number of taps Note there is An error in the below data, used a peers data file with JASP to get correct data. hand

taps 2 2 1 2 2 1 1 1 1 2 1 1 2 2 1 2

141 139 97 118 121 135 213 131 107 124 204 131 158 110 114 141

2 203 1 161 1 126 2 211 1 147 2 111 2 138 1 118 2 158 2 120 1 118 1 117 1 237 2 153 1 130 1 120 2 133 2 125 1 155 2 238 2 174 1 191 1 46 1 152 2 260 1 171 2 155 2 198 Export data so that it can be opened by JASP. File save as .txt file.

Open JASP, open file

Label the data: Click hand (IV) new window should appear, change the value labels in JASP

Change label to IV (left & right)

Choose whether, scale, ordinal or nominal: Click Icon on the variable column at a drop down list will appear. (IV: nominal, DV: scale)

Click Descriptives: Click the DV, the arrow to put it in the variables.

For additional stats, click statistics and choose (medium, mode, skewness & kurtosis)

Click plots, distribution plots etc

Type of statistical test used to analyse this data: T-Tests NOTE: What type of stats do you do in one situation? If you have IV that is categorical and has 2 levels and you have a continuous dependent variable you use a T-Test. Not paired (paired if for within samples) so this is not a paired sample. Categorical IV (2) handness Continuous DV Independent sample T-Test Click T-Test Taps is Variable, hand is grouping variable

Lecutre 2: Interpreting Descriptive Statistics Obtain Information to Mean, Median, Mode: Skewness & Kurtosis

44 valid data Average: 148.864 (Mean) Median (Midpoint): Mode Want to see whether those values are approximately the same as the mean. If they vary significantly from the mean, that would indicate a skew going on in the data (outliers). In this case they are pretty close. SD: how far away average point for the mean (variability in sample). Smaller SD less variability of the sample, greater SD variability more broad stretched out distribution. 2 SD away from mean 98%.

Distribution Plot: Skewness positive (shifted to the right), skewness negative (shifted to the left). Way to know skewness is an issue. Is whether skewness value is more than double standard error of skewness. (Heuristic only – maybe something be a miss). Skew .68 SD of Skew: 0.35. Not quite close to being double. Kurtosis: how pointy or how flat, crazy pointy (everyone did exactly the same thing), have to use different stat methods besides t-tests, anova. More than double = issue. Kurtosis value to not be double the standard error of kurtosis. Minimum & Maximum: to make sure data makes sense. (Check for data entry issues etc.).

Whether pattern of data is consistent with our hypothesis, right hand is superior to left hand dexterity. Is mean higher for right v left hand. Split sample for left hand and right hand. In descriptive stats: Put right hand into the split box.

Interpret Data same way we did previous data Valid Case 23 left, 21 right None missing Mean 144 left, 153, right

Right hand more detxteriuos than left hand. Mean, Mode, Median – Similar. Expecting more pointly distirubtion for right V left, SD similar Skewness: right: 1.360 (check), skewness for left 0.251. Look at distributions

Right: Couple of people high data, 21 cases 4 of those very large. (Tail), skewness index to be higher. Does not bother Matt. Healthy distribution for most of data he thinks. We knew why skewness data is high. Larger number. We want to get understanding and assessment of what data is telling us, right produce more results. Next: T-Test to evaluate whether number of Taps of right was statistically greater, with a significant p value. Classic Independent Sample T-Test.

Taps: Variable (DV) Hand: Grouping Variable (IV)

ALWAYS TICK DESCRIPTIVES BOX

Look at Descriptive Stats First

Whether difference significant: independent sample T-Test. There is NOT a significant difference. Value in which to look is the p value. Statistically different if p0.05, not statistically different, SD so large so much variability can’t see difference between the two group. Probably caused by ultra tappers.

How to report the results of a t-test using APA: t(42) = -0.70, p = .48 2DP. Italicise letters. Only use less than symbol below the .001. New reporting standards report exact P Value.

MATT DOESNT ROUND. CUT OFF INSTEAD. Summary of Stats in 5 Minutes (Which statistic to run – when) Parametric tests when data is normally distributed. (t-tests, anova, regression) -

1 IV with categorical data, 2 levels and continuous DV = independent samples t-test 1 IV with categorical data, 3 levels and continuous DV = 1 way anova. (1way refers to Number of IV). 1 IV with categorical data, 4 levels and continuous DV = 1 way anova (still one IV). Handy for IV with any number of levels (1 IV, with 12 levels still one way anova). 1 IV with categorical data, 3 levels and dichotomous (2 levels) DV (two towers – not normal distrubiton – non-parametric test = Qai Square Test 2 IV with categorical data, continuous DV – 2 way anova. 3 IV each with 2 levels and continuous DV – 3 way anova. (12 IV each with different levels – 12 way anova etc.). 1 continuous IV – and 1 continuous DV = Multiple regression/correlation. (any time continuous IV)...