Research design

Variables

• Independent variable

• Dependent variable

• Levels

• Responses

Variables and conditions

Subjects are given two types of constructions and are asked to decide whether the given sentence is grammatical:

(1) a. I gave him it. Construction 1b. I gave her the book.c. …

(2) a. I gave to him it. Construction 2b. I gave to her the note you sent me.c. …

Variables and conditions

IV (two conditions) DV (forced choice task)

Construction 1Construction 2

a. grammaticalb. ungrammatical

Variables and conditions

Subjects are asked to complete copular sentences with a relative clause. The predicate nominals of the copular clauses belong to three different semantic types: (1) animate/human (2) inanimate/object (3) place.

(1) a. This is the man __ b. This is the ball __c. This is the place __

Variables and conditions

IV DV

1. This is the man __ 2. This is the ball __3. This is the place __

a. SUBJ relative clauseb. DO relative clausec. IO relative claused. OBL relative clausee. GEN relative clause

Variables and conditions

IV DV

1. This is the man __ 2. This is the thing __3. This is the place __

a. SUBJ relative clauseb. DO relative clausec. IO relative claused. OBL relative clausee. GEN relative clause1. I saw the man __

2. I saw the thing __3. I saw the place __

Interaction

Condition 1 Condition 2

SUBJ 3.5DO 3.2IO 2.7OBL 2.2GEN 0.6

SUBJ 2.5DO 3.8IO 3.2OBL 0.5GEN 0.5

Types of data

• Nominal/categorical data

• Ordinal data

• Interval data

Type of analysis

• Correlational analysis

• Difference test

Type of analysis

Correlational test Difference test

Pearson‘s rKendall‘s tau

T-testANOVA

Confound variable

(1) … the man who talked to Mary.

(2) … the car that caused the accident.

(3) … the man who Mary talked to.

(4) … the car that Peter bought.

Confound variable

(1) … the man who talked to Mary.

(2) … the car that caused the accident.

(3) … the man who Mary talked to.

(4) … the car that Peter bought.

Confound variables

• Control

• Randomization

Sampling

• Simple random sampling

• Stratified random sampling

• Systematic sampling

• Cluster sampling

Related and independent design

• Within subjects design – related design – repeated measures design

• Between subjects design – unrelated design – independent design

Advantages of within subjects design

• Reduction of inter-individual differences

• Fewer subjects

Disdvantages of within subjects design

• Subjects recognize the purpose of the study.

• Subjects get tired, frustrated, excited.

• Subjects get habituated to the task.

Responses to IVs/conditions can influence each

other:

Counterbalancing

• ABBA

• AB - BA

Counterbalancing serves to eliminate the

ordering effect.

Counterbalancing

1.ABC

2.ACB

3.BAC

4.CAB

5.BCA

6.CBA

Experimental design

A child language researcher wants to find out if the

meaning of the head of a relative clause influences the

interpretation of the acquisition of relative clauses in

early child speech. Specifically, he wants to know if

animate and inanimate head nouns affect children’s

interpretation of relative clauses. In this study, he

concentrates on the two most frequent types of relative

clauses in which the subject and object are relativized

(i.e. expressed by the relative pronoun).

Experimental design

(1) Das ist der Mann, der das Mädchen gestern gesehen hat.

(2) Das ist der Mann, den das Mädchen gestern gesehen hat.

(3) Das ist der Ball, der das Mädchen am Kopf getroffen hat.

(4) Das ist der Ball, den das Mädchen mit dem Kopf getroffen hat.

Experimental design

(1) Das ist der Mann, der das Mädchen gestern gesehen hat.

(2) Das ist der Mann, den das Mädchen gestern gesehen hat.

(3) Das ist der Ball, der das Mädchen am Kopf getroffen hat.

(4) Das ist der Ball, den das Mädchen mit dem Kopf getroffen hat.

Experimental design

Animate head Inanimate head

Subject

Object

Central tendency

Data: 2, 3, 3, 3, 4, 6, 6, 9, 12, 13, 13

Mean: 2+3+3+3+4+6+6+9+12+13+13

11= 6.72

Median: 2, 3, 3, 3, 4, 6, 6, 9, 12, 13, 13 = 6

Mode: 2, 3, 3, 3, 4, 6, 6, 9, 12, 13, 13 = 3

Variance and SD

(x1 – x)2

N- 1

Variance

S words

12345678

3749129114

Variance

S words

12345678

3749129114

59 / 8 = 7.4 (mean)

Variance

S words (=X1 – Xmean)

12345678

3749129114

3 – 7.4 7 – 7.44 – 7.49 – 7.412 – 7.49 – 7.411 – 7.44 – 7.4

59 / 8 = 7.4 (mean)

Variance

S words (=X1 – Xmean) d1

12345678

3749129114

3 – 7.4 7 – 7.44 – 7.49 – 7.412 – 7.49 – 7.411 – 7.44 – 7.4

–4.4–0.4–3.41.64.61.63.6–3.4

59 / 8 = 7.4 (mean)

Variance

S words (=X1 – Xmean) d1

12345678

3749129114

3 – 7.4 7 – 7.44 – 7.49 – 7.412 – 7.49 – 7.411 – 7.44 – 7.4

–4.4–0.4–3.41.64.61.63.6–3.4

59 / 8 = 7.4 (mean)

0 / 8 = 0

Variance

S words (=X1 – Xmean) d1 d12 (residuals)

12345678

3749129114

3 – 7.4 7 – 7.44 – 7.49 – 7.412 – 7.49 – 7.411 – 7.44 – 7.4

–4.4–0.4–3.41.64.61.63.6–3.4

19.360.1611.562.5621.162.5612.9611.56

59 / 8 = 7.4 (mean)

0 / 8 = 0 81.87

Variance

81.87

8 - 1= 11.7

Standard Deviation

81.87

8 - 1= 3.42

Standard Deviation

70% of all data points fall within 1 SD.

Mean +/- SD = range of 70% of the data

7.4 +/- 3.42 = 3.98 – 10.82 words